Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114 was filed in this application after a decision by the Patent Trial and Appeal Board, but before the filing of a Notice of Appeal to the Court of Appeals for the Federal Circuit or the commencement of a civil action. Since this application is eligible for continued examination under 37 CFR 1.114 and the fee set forth in 37 CFR 1.17(e) has been timely paid, the appeal has been withdrawn pursuant to 37 CFR 1.114 and prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant’s submission filed on 09/26/2025 has been entered.
Notice to Applicant
This communication is in response to the amendment filed 09/26/2025. Claim 1 has been amended. Claim 20 has been canceled. Claims 1-11, 14-17 are presented for examination.
Specification
The disclosure is objected to because of the following informalities:
In ¶ 0063, “Random Forrest” seems to be a grammatical error. Examiner recommends amending it to read -- Random For[[r]]est –.
Appropriate correction is required.
Claim Objections
Claim 1 is objected to because of the following informalities:
In claim 1, line(s) 29-30, the terms “XG Boost,” “SVM,” “LSTM,” “SARIMA,” and “RNN” are not previously defined. Examiner recommends defining the aforementioned terms at the first instance of the acronyms. Examiner suggests amending it to read – XG Boost (eXtreme Gradient Boosting) --, -- SVM (Support Vector Machine) --, -- LSTM (Long Short-Term Memory) --, -- SARIMA (Seasonal Autoregressive Integrated Moving Average) --, -- RNN (Recurrent Neural Network) --, respectively.
In claims 1, line(s) 29, “Random Forrest” seems to be a grammatical error. Examiner recommends amending it to read – Random For[[r]]est --.
Appropriate correction is required.
Subject Matter Free of Prior Art
Claim(s) 1-11, 14-17 are allowable over prior art because the prior art of record fail to expressly teach or suggest, either alone or in combination, the features found within the independent claims, in particular: “based on such processing, retrieving a mapping information for the one or more medical procedures, relational information, seasonality of medical requirements data, stock database indicative of inventory and including a threshold data and an indicator, and a historical information for the one or more medical procedures from a memory device, wherein the historical information includes a consumption deviation data related to deviation in consumption of inventory items in the past and a requirement variation data related to deviation between the inventory forecast and the order placed in the past,” “processing the mapping information and the historical information by the processing unit, and automatically generating at least one or more combinations of an inventory forecast related to the inventory of items required by the one or more medical facilities, or a procedure forecast related to a number of medical procedures to be taking place in the one or more medical facilities, a specific medical facility forecast, a disease outbreak forecast, a safety inventory forecast, a cumulative inventory forecast related to the inventory of items required by the one or more medical facilities and a cumulative procedure forecast related to the number of procedures to be taking place in the one or more medical facilities.” Because the prior art does not teach or disclose the above features in the specific manner and combinations recited in independent claim 1, claim 1 is hereby deemed to be allowable over prior art. Originally numbered dependent claims 2-11, 14-17 incorporate the allowable features of originally numbered independent claim 1 through dependency.
However, the claims are still rejected under 101.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-11, 14-17 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "the stock database" in line 52. There is insufficient antecedent basis for this limitation in the claim. Claim 1 previously recites “a stock database” in line 41 and amended claim 1 now recites a “stock database” in lines 8-9. Are they the same “stock database” or different? If they are different, Examiner recommends numbering the different stock databases (i.e., first, second, etc. stock database). Appropriate clarification is requested for the proper interpretation of the claim limitations, as the ambiguity renders the metes and bounds of the claim unclear. For examination purposes, Examiner interprets “the stock database” as: the “stock database” of line 41.
Claim(s) 2-11, 14-17 is/are rejected as being dependent on claim 1.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-11, 14-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Based upon consideration of all of the relevant factors with respect to the claims as a whole, the claims are directed to non-statutory subject matter which do not include additional elements that are sufficient to amount to significantly more than the judicial exception because of the following analysis:
Claim 1 is drawn to a method which is within the four statutory categories (i.e., method).
Independent claim 1 recites…receiving a user input related to one or more medical procedures…, wherein the user input comprises identification information related to one or more medical facilities for which a forecast is to be generated; receiving and processing the user input…, and based on such processing, retrieving a mapping information for the one or more medical procedures, relational information, seasonality of medical requirements data, stock database indicative of inventory and including a threshold data and an indicator, and a historical information for the one or more medical procedures…, wherein the historical information includes a consumption deviation data related to deviation in consumption of inventory items in the past and a requirement variation data related to deviation between the inventory forecast and the order placed in the past, and wherein the threshold data relates to one or more thresholds of quantity of an item required to be kept in the inventory, and the indicator being a level indicator giving visual information to the user regarding stock available for a particular item in the inventory; processing the mapping information and the historical information…, and automatically generating at least one or more combinations of an inventory forecast related to the inventory of items required by the one or more medical facilities, or a procedure forecast related to a number of medical procedures to be taking place in the one or more medical facilities, a specific medical facility forecast, a disease outbreak forecast, a safety inventory forecast, a cumulative inventory forecast related to the inventory of items required by the one or more medical facilities and a cumulative procedure forecast related to the number of procedures to be taking place in the one or more medical facilities…, wherein the one or more combinations of the forecasts are generated for multiple time intervals, wherein the mapping information relates to mapping between a medical procedure of the one or more medical procedures and the inventory of items required to carry out the one or more medical procedures, and wherein the mapping information is dynamically updated based on an editing input received…, the historical information is related to consumption of items in past for the one or more medical procedures... said historical information being of medical facilities for a dynamically configurable geographical area having a radius based on which the forecasts are fine-tuned for medical facilities that form part of said configurable geographical area; retrieving a current stock information… based on processing the mapping information, wherein the current stock information is related to quantities of each inventory-item in the stock; and processing the current stock information along with the at least one of: the inventory forecast, or the procedure forecast, or a combination thereof…and generating a list of items required to be ordered, wherein the list of items are generated…based on the historical information, the current stock information, the relational information, the seasonality of medical requirements data, the inventory, the threshold data, the indicator, and the mapping information, wherein the stock [information] is defined by quantities of each item present in the inventory.
Under its broadest reasonable interpretation, the limitations noted above, as drafted, covers certain methods of organizing human activity (i.e., managing personal behavior or relationships or interactions between people…following rules or instructions), but for the recitation of generic computer components. That is, other than reciting a “input unit,” “processing unit,” the claim encompasses rules or instructions followed to forecast and manage resources (i.e., inventory) in a medical facility. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people, but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Claim 1 recites additional elements (i.e., input unit; processing unit; memory device storing a historical database; a decision-tree-based ensemble Machine Learning mechanism… wherein the decision-tree-based ensemble Machine Learning mechanism is selected from any or a combination of XG Boost mechanism, Random Forrest, SVM, LSTM, SARIMA, Gated Recurrent Units, and RNN mechanism; a stock database stored in the memory device). Looking to the specifications, a computing device having an input unit, processing unit, memory device storing databases is described at a high level of generality (¶ 0051-0053; ¶ 0066), such that it amounts to no more than mere instructions to apply the exception using generic computer components. Furthermore, a “decision-tree-based ensemble Machine Learning mechanism…selected from any or a combination of XG Boost mechanism, Random Forrest, SVM, LSTM, SARIMA, Gated Recurrent Units, and RNN mechanism” is described at a high level of generality (¶ 0063), such that it is only used to generally apply the abstract idea without placing any limits on how the machine learning mechanism functions and only recite the outcome of the abstract idea and does not include details about how “forecast future stock requirements” is accomplished, and thus, provide nothing more than mere instructions to implement an abstract idea on a generic computer, and merely indicates a field of use or technological environment (i.e., machine learning) in which the judicial exception is performed. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. The additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, the claims are directed to an abstract idea.
Reevaluated under step 2B, the additional elements noted above do not provide “significantly more” when taken either individually or as an ordered combination. As previously analyzed, the use of a general purpose computer or computers (i.e., a computing device having an input unit, processing unit, memory device storing databases) amounts to no more than mere instructions to apply the exception using generic computer components and does not impose any meaningful limitation on the computer implementation of the abstract idea, so it does not amount to significantly more than the abstract idea. Furthermore, a “decision-tree-based ensemble Machine Learning mechanism…selected from any or a combination of XG Boost mechanism, Random Forrest, SVM, LSTM, SARIMA, Gated Recurrent Units, and RNN mechanism” is only used to generally apply the abstract idea without placing any limits on how the machine learning mechanism functions and only recite the outcome of the abstract idea and does not include details about how “forecast future stock requirements” is accomplished, and thus, provide nothing more than mere instructions to implement an abstract idea on a generic computer, and merely indicates a field of use or technological environment (i.e., machine learning) in which the judicial exception is performed. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. The combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology and their collective functions merely provide a conventional computer implementation of the abstract idea. Furthermore, the additional elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than a recitation of generally linking the abstract idea to a particular technological environment or field of use, as the courts have found in Parker v. Flook; similarly, the current invention merely limits the claimed calculations to the healthcare industry which does not impose meaningful limits on the scope of the claim. Therefore, there are no limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception.
Dependent claims 2-11, 14-17 include all the limitations of the parent claims and further elaborate on the abstract idea discussed above and incorporated herein.
Claims 2-11, 14-17 further define the analysis and organization of data for the performance of the abstract idea and do not recite any additional elements. Thus, the claims do not integrate the abstract idea into a practical application and do not provide “significantly more.”
Although the dependent claims add additional limitations, they only serve to further limit the abstract idea by reciting limitations on what the information is and how it is received and used. These information characteristics do not change the fundamental analogy to the abstract idea grouping of “Certain Methods of Organizing Human Activity,” and, when viewed individually or as a whole, they do not add anything substantial beyond the abstract idea. Furthermore, the combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology. Therefore, the claims when taken as a whole are ineligible for the same reasons as the independent claims.
Response to Arguments
Applicant's arguments filed 09/26/2025 have been fully considered but they are not persuasive. Applicant’s arguments will be addressed hereinbelow in the order in which they appear in the response filed 09/26/2025.
In the remarks, Applicant argues in substance that:
Regarding the 101 rejections,
“the limitations of the independent claim 1 as a whole, do not fall within the mental processes grouping of abstract ideas under Prong One of the Revised Step 2A as they, as mentioned above, clearly contain steps that cannot be performed by human mind specially the steps of processing the user input by a processing unit to as to retrieve mapping information pertaining to medical procedures, relational information, seasonality of medical requirements data, stock database indicative of inventory and including a threshold data and an indicator, and historical information for the one or more medical procedures, and therefore it won't be feasible for any user to consider all such parameters so as to determine the mapping information. Also, use of the threshold data associated with quantity of an item required to be kept in the inventory, and an indicator associated with a level indicator giving visual information to the user regarding stock available for a particular item in the inventory, cannot be undertaken by the user along with the above-mentioned identified features of the present invention. Independent claim therefore is not directed to a mental process, but instead relates to a specific implementation of automatically forecasting one or more items based on historical information and other associated parameters including reference to the past medical procedures that have been undertaken, and therefore owing to such automatic prediction in view of numerous parameters as claimed with an ability to be dynamically configurable based on geographical region is what makes the invention clear an implementation that cannot be practically performed in the human mind”;
“processing of the user input by a processing unit to as to retrieve mapping information pertaining to medical procedures, relational information, seasonality of medical requirements data, stock database indicative of inventory and including a threshold data and an indicator, and historical information for the one or more medical procedures, and using said information/mapping to determine forecasts for one or more items to be used in medical procedures is clearly resulting in a practical application for dynamically forecasting, that too where the historical information is associated with medical facilities for a dynamically configurable geographical area having a radius based on which the forecasts are fine-tuned for medical facilities that form part of said configurable geographical area. Further practical application is brought upon by processing the current stock information along with the at least one of: the inventory forecast, or the procedure forecast, or a combination thereof, by the processing unit, and generating a list of items required to be ordered, wherein the list of items are generated by the processing unit based on the historical information, the current stock information, the relational information, the seasonality of medical requirements data, the inventory, the threshold data, the indicator, and the mapping information. In other words, while the end goal of the invention results in prediction of forecast for one or more items, said method of determination of said prediction is based on clearly technical steps including the parameters based on which the determination is done, geographical limits/limitations in which said determination is done, among other practical and technical steps as mentioned/identified above including but not limited to use of a decision-tree-based ensemble Machine Learning mechanism to forecast future item requirements, wherein the decision-tree-based ensemble Machine Learning mechanism is selected from any or a combination of XG Boost mechanism, Random Forrest, SVM, LSTM, SARIMA, Gated Recurrent Units, and RNN mechanism... The claims therefore clearly improve the technology or technical field in the invention by more accurately undertaking the medical item forecasting based on how/when medical procedures are undertaken along with several other information such as historical information and seasonality attributes.”
It is respectfully submitted that Examiner has considered Applicant’s arguments and does not find them persuasive. Examiner has attempted to address all of the arguments presented by Applicant; however, any arguments inadvertently not addressed are not persuasive for at least the following reasons:
In response to Applicant’s argument that (a) regarding the 101 rejections,
“the limitations of the independent claim 1 as a whole, do not fall within the mental processes grouping of abstract ideas under Prong One of the Revised Step 2A as they, as mentioned above, clearly contain steps that cannot be performed by human mind specially the steps of processing the user input by a processing unit to as to retrieve mapping information pertaining to medical procedures, relational information, seasonality of medical requirements data, stock database indicative of inventory and including a threshold data and an indicator, and historical information for the one or more medical procedures, and therefore it won't be feasible for any user to consider all such parameters so as to determine the mapping information. Also, use of the threshold data associated with quantity of an item required to be kept in the inventory, and an indicator associated with a level indicator giving visual information to the user regarding stock available for a particular item in the inventory, cannot be undertaken by the user along with the above-mentioned identified features of the present invention. Independent claim therefore is not directed to a mental process, but instead relates to a specific implementation of automatically forecasting one or more items based on historical information and other associated parameters including reference to the past medical procedures that have been undertaken, and therefore owing to such automatic prediction in view of numerous parameters as claimed with an ability to be dynamically configurable based on geographical region is what makes the invention clear an implementation that cannot be practically performed in the human mind”:
It is respectfully submitted that per broadest reasonable interpretation of the claim in light of the specification, the claims of the present invention (including the limitations to which Applicant seem to refer as “the steps of processing the user input by a processing unit to as to retrieve mapping information pertaining to medical procedures, relational information, seasonality of medical requirements data, stock database indicative of inventory and including a threshold data and an indicator, and historical information for the one or more medical procedures…use of the threshold data associated with quantity of an item required to be kept in the inventory, and an indicator associated with a level indicator giving visual information to the user regarding stock available for a particular item in the inventory”) encompass the activity of (to paraphrase) rules or instructions followed to forecast and manage resources (i.e., inventory) in a medical facility, which covers the sub-grouping of managing personal behavior or relationships or interactions between people in the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, and not a concept performed in the human mind in the “Mental Processes” grouping, as Applicant now argues. Put another way, the claimed invention amounts to a series of rules or steps that a user (i.e., inventory manager, administrator) would follow to collect, analyze, and output data regarding inventory levels. This is an abstract idea. That the steps are performed on one or more well-known, general purpose computer (i.e., a computing device having an input unit, processing unit, memory device storing databases) does not remove the invention from being directed to an abstract idea.
Thus, the claims recite an abstract idea.
“processing of the user input by a processing unit to as to retrieve mapping information pertaining to medical procedures, relational information, seasonality of medical requirements data, stock database indicative of inventory and including a threshold data and an indicator, and historical information for the one or more medical procedures, and using said information/mapping to determine forecasts for one or more items to be used in medical procedures is clearly resulting in a practical application for dynamically forecasting, that too where the historical information is associated with medical facilities for a dynamically configurable geographical area having a radius based on which the forecasts are fine-tuned for medical facilities that form part of said configurable geographical area. Further practical application is brought upon by processing the current stock information along with the at least one of: the inventory forecast, or the procedure forecast, or a combination thereof, by the processing unit, and generating a list of items required to be ordered, wherein the list of items are generated by the processing unit based on the historical information, the current stock information, the relational information, the seasonality of medical requirements data, the inventory, the threshold data, the indicator, and the mapping information. In other words, while the end goal of the invention results in prediction of forecast for one or more items, said method of determination of said prediction is based on clearly technical steps including the parameters based on which the determination is done, geographical limits/limitations in which said determination is done, among other practical and technical steps as mentioned/identified above including but not limited to use of a decision-tree-based ensemble Machine Learning mechanism to forecast future item requirements, wherein the decision-tree-based ensemble Machine Learning mechanism is selected from any or a combination of XG Boost mechanism, Random Forrest, SVM, LSTM, SARIMA, Gated Recurrent Units, and RNN mechanism... The claims therefore clearly improve the technology or technical field in the invention by more accurately undertaking the medical item forecasting based on how/when medical procedures are undertaken along with several other information such as historical information and seasonality attributes”:
Applicant argues “a practical application for dynamically forecasting” and “more accurately undertaking the medical item forecasting.” However, as stated previously in Office Action dated 06/26/2025, “forecasting” addresses an administrative problem, and not a technical problem to any specific devices, technology, or computers for that matter, and thus, the claims do not provide a technical solution. Furthermore, the claim limitations to which Applicant seem to refer as providing the alleged improvements (i.e., “processing of the user input by a processing unit to as to retrieve mapping information pertaining to medical procedures, relational information, seasonality of medical requirements data, stock database indicative of inventory and including a threshold data and an indicator, and historical information for the one or more medical procedures, and using said information/mapping to determine forecasts for one or more items to be used in medical procedures,” “where the historical information is associated with medical facilities for a dynamically configurable geographical area having a radius based on which the forecasts are fine-tuned for medical facilities that form part of said configurable geographical area,” “processing the current stock information along with the at least one of: the inventory forecast, or the procedure forecast, or a combination thereof, by the processing unit, and generating a list of items required to be ordered, wherein the list of items are generated by the processing unit based on the historical information, the current stock information, the relational information, the seasonality of medical requirements data, the inventory, the threshold data, the indicator, and the mapping information,” “parameters based on which the determination is done, geographical limits/limitations in which said determination is done,” “how/when medical procedures are undertaken along with several other information such as historical information and seasonality attributes”) are interpreted as rules or instructions to forecast and manage resources (i.e., inventory) in a medical facility, which is the abstract idea, but for the recitation of generic computer components. Therefore, even if the claims provide the aforementioned alleged improvements, these alleged benefits are at best, an improvement to the abstract idea. However, an improved abstract idea is still an abstract idea.
Furthermore, the “use of a decision-tree-based ensemble Machine Learning mechanism to forecast future item requirements, wherein the decision-tree-based ensemble Machine Learning mechanism is selected from any or a combination of XG Boost mechanism, Random Forrest, SVM, LSTM, SARIMA, Gated Recurrent Units, and RNN mechanism” is described at a high level of generality (¶ 0063), such that it is only used to generally apply the abstract idea without placing any limits on how the machine learning mechanism functions and only recite the outcome of the abstract idea and does not include details about how “forecast future stock requirements” is accomplished, and thus, provide nothing more than mere instructions to implement an abstract idea on a generic computer, and merely indicates a field of use or technological environment (i.e., machine learning) in which the judicial exception is performed. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually.
As stated previously in Office Action dated 06/26/2025, the computing system did not cause the argued problem and thus it is not a technical problem caused by the technological environment to which the claims are confined. Even a technical solution to a non-technical problem does not integrate the judicial exception into a practical application. Applicant’s claims do not recite the invention of improvements to computer functionality, technology, or any other technological field, but the use of generic computer components (i.e., a computing device having an input unit, processing unit, memory device storing databases) to forecast and manage resources (i.e., inventory) in a medical facility, which is an abstract idea, but for the recitation of generic computer components. Examiner cannot find and Appellant has not identified any problem caused by the technological environment to which the claims are confined (i.e., a well-known, general purpose computer). While the specification need not explicitly set forth the improvement, the disclosure does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing any technical improvement to computer technology, a physical improvement to the computer, or any other technical improvement. See MPEP § 2106.04(d)(1) and 2106.05(a).
Thus, the claim as a whole does not integrate the recited judicial exception into a practical application.
Reevaluated under step 2B, the additional elements noted above do not provide “significantly more” when taken either individually or as an ordered combination. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually.
Thus, the claim as a whole does not amount to significantly more than the judicial exception.
Thus, Examiner maintains the 101 rejections of claims 1-11, 14-17, which have been updated to address Applicant’s remarks and to comply with the 2019 Revised Patent Subject Matter Eligibility Guidance and the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence in the above Office Action.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Emily Huynh whose telephone number is (571)272-8317. The examiner can normally be reached on M-Th 8-5 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert Morgan can be reached on (571) 272-6773.The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/EMILY HUYNH/Primary Examiner, Art Unit 3683