DETAILED ACTION
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 .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cao (CN 109801716 A) in view of Huang (TW M570475 U), and in view of Jain (PGPUB: 20150081321 A1).
Regarding claim 1. Cao teaches a method for reading an optical prescription on an optical prescription image, the method comprising:
detecting a region comprising the optical prescription on the optical prescription image (see page 3, lines 14-16, for the doctor not typing, handwriting can be input by OCR character recognizing module, doctor confirm prescription, patient WeChat public account doctor, the patient receiving the prescription order after the order payment and filling information according to the order information and delivery to the patient);
extracting the optical prescription (see page 5, lines 25-37, the extraction of the invention system, a patient needs to log WeChat and hospital of interest WeChat public account, the doctor needs to download mobile phone APP client end and application authentication platform formal doctor, on-line can be used all of the doctor end function and the system management platform is pre-set with medicine standard font, using shooting function through the authentication submission qualification, if handwriting character of doctor comparing neat specification, then this function can be directly used without any problem, but if the handwriting font of the doctor is special. handwritten name is needed, each kind of medicine at least 3 script, and the photograph uploaded to the system for storage in advance. the doctor and patient communication and confirmation condition, for mobile phone operation of doctor, can directly typing by mobile phone recording, for not familiar mobile phone operation of doctor, prescription can be handwritten and select the shooting function) and converting the optical prescription into machine-encoded optical prescription data (see page 6 and 7, lines 36-38 and 1-4, using the photographing function, the doctor for mobile phone camera finishing shooting action of the handwritten prescription, at this time, if not selected, the automatic identification module performs image recognition, OCR character identification module for reading the photograph, analyzing the text, and using the analyzed character to compare with medicine word storage unit in the drug library, the contrast medicine automatically recorded into the open interface of the system).
Huang teaches that a prescription, optical character recognition management system of the present invention comprises a first vehicle and a second vehicle, the second vehicle having a shooting unit, a text recognition unit and a text data classification unit, wherein the shooting unit is configured to capture a Forming a prescription file, the character recognition unit is configured to identify a plurality of characters of the prescription image file, and the text data classification unit is configured to classify and store the characters in a plurality of predetermined fields, and Forming a text file, the second vehicle transmits the prescription file and the text file to the first carrier (see page 3, lines 5-12).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Cao by Huang to obtain the character recognition unit is configured to identify a plurality of characters of the prescription image file, and the text data classification unit is configured to classify and store the characters in a plurality of predetermined fields, and Forming a text file, the second vehicle transmits the prescription file and the text file to the first carrier, in order to provide classifying a portion of the optical prescription data into one or more predetermined categories, to generate an optical prescription value associated with a respective one of the one or more predetermined categories. Therefore, combining the elements from prior arts according to known methods and technique would yield predictable results.
However, Cao does not expressly teach:
classifying a portion of the optical prescription data into one or more predetermined categories, to generate an optical prescription value associated with a respective one of the one or more predetermined categories; and
However, the combination does not expressly teach determining whether the optical prescription value associated with the respective one of the one or more predetermined categories contains an error, and, if the optical prescription value contains the error, correcting the error within the optical prescription value, to generate a corrected optical prescription value associated with the respective one of the one or more predetermined categories.
Jain teaches that the identification of unstructured units and the categorization of unstructured units may be performed simultaneously, and in others the method may comprise identifying units of unstructured data, categorizing the unstructured units, and re-executing the identification rules, algorithms, and/or steps to re-identify units of any remaining unstructured data. For example, a typographical error in the term "p.r.n." adding a space may result in identification of "p." and "r.n." as separate units that do not meet any categorization rules, but when the initial categorization fails the method may comprise joining remaining adjacent units of unstructured data to determine if, when joined, the joined unstructured unit may be categorized. In some examples, the joining is performed as an initial step or an additional step in the initial identification process (i.e. in this example both "p." and "r.n." and the combined term "p.r.n." could be initially identified for subsequent categorization) (see paragraph 50); the rules may result in recognizing and correcting typographical errors. In various embodiments, the rules may result in recognizing partial information included in the prescription information and converting and/or supplementing the partial information to a more detailed and/or a different form. In certain examples, the normalization and disambiguating is subsumed in the steps of the language processing logic execution (see paragraph 48).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination by Jain to obtain a typographical error in the term "p.r.n." adding a space may result in identification of "p." and "r.n." as separate units that do not meet any categorization rules, but when the initial categorization fails the method may comprise joining remaining adjacent units of unstructured data to determine if, when joined, the joined unstructured unit may be categorized. In some examples, the joining is performed as an initial step or an additional step in the initial identification process (i.e. in this example both "p." and "r.n." and the combined term "p.r.n." could be initially identified for subsequent categorization), in order to provide determining whether the optical prescription value associated with the respective one of the one or more predetermined categories contains an error, and, if the optical prescription value contains the error; and further to obtain the rules may result in recognizing and correcting typographical errors. In various embodiments, the rules may result in recognizing partial information included in the prescription information and converting and/or supplementing the partial information to a more detailed and/or a different form. In certain examples, the normalization and disambiguating is subsumed in the steps of the language processing logic execution, in order further to provide correcting the error within the optical prescription value, to generate a corrected optical prescription value associated with the respective one of the one or more predetermined categories. Therefore, combining the elements from prior arts according to known methods and technique would yield predictable results.
Regarding claim 2. The combination teaches the method of claim 1, wherein
the detecting the region comprising the optical prescription on the optical prescription image comprises detecting at least one keyword and the portion of the optical prescription data associated with the at least one keyword (see Fig. 1-4, Huang, page 4, lines 1-7, the second carrier 120 classifies and stores the characters A11 in a plurality of predetermined fields B by the text data classification unit 123, and forms a text data file B1, and the text data file. B1 appears in the second carrier 120, and the predetermined field B is selected from the date, the name column, the ID number column, the health care drug code, the drug name and specification, the product name, the dosage form, the ingredient name, the usage, and the number of days of administration),
wherein detecting the at least one keyword comprises detecting the at least one keyword and a corresponding one or more erroneous keywords associated with a respective one of the at least one keyword (see Jain, paragraph 50, a typographical error in the term "p.r.n." adding a space may result in identification of "p." and "r.n." as separate units that do not meet any categorization rules, but when the initial categorization fails the method may comprise joining remaining adjacent units of unstructured data to determine if, when joined, the joined unstructured unit may be categorized. In some examples, the joining is performed as an initial step or an additional step in the initial identification process (i.e. in this example both "p." and "r.n." and the combined term "p.r.n." could be initially identified for subsequent categorization) . As another representative example, related or complimentary terms may be joined together, for example the term "empty" near the term "stomach" may result in joining and ultimately categorizing these terms together in the food administration category); and
extracting the optical prescription comprises extracting the at least one keyword and the portion of the optical prescription data associated with the at least one keyword (see Jain, paragraph 41, the user takes a picture or otherwise scans a label of the prescription medicine and the instructions are determined via optical character recognition or similar processes designed to extract the textual information from the image).
Allowable Subject Matter
Claims 3-15 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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/XIN JIA/Primary Examiner, Art Unit 2663
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