DETAILED ACTION
This communication is responsive to RCE/Amendment filed 10/30/2025.
Claims 1-22 are pending in this application. In the Amendment, claim 1 is amended.
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 .
Response to Arguments
Applicant’s arguments with respect to claims amended 10/30/2025 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claims 1-6, 12-15 and 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over Ozeran (US 2020/0335188) in view of Tamilarasan et al. (“Tamilarasan”, US 2017/0286388).
As per claim 1, Ozeran teaches a method comprising:
displaying a first clinical report having a type (Ozeran, Fig.2, 26, para.158, 184, 201-205, templates particular to disease type; reports associated with project type), wherein the first clinical report is in an unstructured electronic file format (Ozeran, para.184, Fig.2, second panel 220 displays raw documents);
displaying, via a graphical user interface (Ozeran, Fig.26, 33, TEMPLATES interface; para.203-204, 210-211), a skeleton report template that enables a user to select (Ozeran, Fig.34-35, para.214, user may select fields 3430), from a plurality of elements of a reference information model (Ozeran, Fig.35, para.214, elements for medical group), a subset of the plurality of elements for inclusion in a custom data model for clinical reports of the type (Ozeran, para.214, subset of elements selected for template project), wherein the graphical user interface is further configured to enable the user to map non-machine readable information from the first clinical report to the elements of the custom data model whereby the non-machine readable information is extracted from the first clinical report and stored in machine-readable form in a first converted clinical report compliant with the reference information model (Ozeran, para.181, 184, 201-205, 263, 348, data abstractor converts non-machine readable information i.e. raw clinical data to structured data specified by template; pre-populate certain fields with extracted data); and
using the custom data model to generate a second converted clinical report compliant with the reference information model that contains, in machine-readable form, non-machine-readable information from the second clinical report (Ozeran, para.201-205, 263, data abstractor converts non-machine readable information i.e. raw clinical data to structured data specified by template; pre-populate certain fields with extracted data).
However, Ozeran does not explicitly teach generating, based on the user selections and the user mapping, the custom data model and parsing a second clinical report of the type. Tamilarasan teaches a method of generating reports and custom templates, based on the user selections and user mapping, and parsing a second clinical report of the type (Tamilarasan, para.20, 27, 43, 45-46, 49, 51 custom template 124 used to generate reports; predictive mapper serially maps extracted fields from source to custom template). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include Tamilarasan’s teaching with Ozeran’s method in order to efficiently map elements from unstructured data to structured data.
As per claim 2, the method of Ozeran and Tamilarasan teaches the method of claim 1, wherein the parsing of a second clinical report of the type includes selecting the custom data model and the second clinical report (Tamilarasan, para.20, 27, 43, 45-46, 49, 51 custom template 124 used to generate reports; predictive mapper serially maps extracted fields from source to custom template), and information from the first converted clinical report, in connection with the custom data model, to automatically extract the non-machine readable information from the second clinical report and store the extracted information in machine-readable form in a second converted clinical report compliant with the reference information model (Ozeran, para.203-205, 228-229, documents associated with project are automatically associated with template).
As per claim 3, the method of Ozeran and Tamilarasan teaches the method of claim 1, wherein the parsing of a second clinical report of the type includes displaying the second clinical report, and, upon selection of the custom data model (Tamilarasan, para.20, 27, 43, 45-46, 49, 51 custom template 124 used to generate reports; predictive mapper serially maps extracted fields from source to custom template), enabling the Graphical User Interface for mapping, responsive to user inputs, non-machine-readable information from the second clinical report to the elements of the custom data model for generating the second converted clinical report (Ozeran, para.181, 184, 203-205, data abstractor converts non-machine readable information i.e. raw clinical data to structured data specified by selected template; pre-populate certain fields with extracted data).
As per claim 4, Ozeran teaches a computing system comprising at least one processor and at least one memory storing instructions which when executed by the at least one processor cause the computing system (Ozeran, para.169, Fig.1, system 100) to:
display a graphical user interface (Ozeran, Fig.26, 33, TEMPLATES interface; para.203-204, 210-211) configured to enable a user to select clinical information fields stored in a default data model (Ozeran, Fig.34-35, para.214, user may select fields 3430);
display a first clinical report document of a given type via a graphical user interface (Ozeran, Fig.2, 26, para.158, 184, 201-205, templates particular to disease type; reports associated with project type), the first clinical report containing corresponding clinical information fields (Ozeran, Fig.2, 26, para.184, 201-205, reports contain clinical fields); and
store computer-readable instructions for implementing a data ingestion tool and a data model generator via the processor (Ozeran, para.167, 169, 228-229, 266, 348, microservices for ingestion, source-specific schema/models);
wherein the data model generator is configured to generate a clinical report data model (Ozeran, templates are models; Fig.26, 33-35, TEMPLATES interface; para.203-204, 210-211, 214, user may select fields 3430, subset of elements selected for template project),
wherein the data ingestion tool is configured to utilize the generated clinical report data model to guide the user through a streamlined mapping process upon receipt of additional clinical reports of the given type (Ozeran, para.181, 184, 201-205, 263, 348, data abstractor converts non-machine readable information i.e. raw clinical data to structured data specified by template; pre-populate certain fields with extracted data).
However, Ozeran does not explicitly teach to generate a clinical report data model by guiding a user, via the graphical user interface and the displayed first clinical report, through a sequential report mapping process. Tamilarasan teaches a system of generating reports configured to generate a clinical report data model by guiding a user, via the graphical user interface and the displayed first clinical report, through a sequential report mapping process (Tamilarasan, para.20, 27, 43, 45-46, 49, 51 custom template 124 used to generate reports; predictive mapper serially maps extracted fields from source to custom template). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include Tamilarasan’s teaching with Ozeran’s system in order to customize mapping elements from unstructured data to structured data to user preferences.
As per claim 5, the system of Ozeran and Tamilarasan teaches the system of claim 4, wherein the sequential report mapping process involves prompting the user, via the graphical user interface, to select the clinical information fields stored in the default data model (Ozeran, Fig.34-35, para.214, user may select fields 343) and map the clinical information fields to the corresponding clinical information fields embodied in the first clinical report (Ozeran, para.181, 184, 201-205, 263, 348, data abstractor converts non-machine readable information i.e. raw clinical data to structured data specified by template).
As per claim 6, the system of Ozeran and Tamilarasan teaches the system of claim 5, wherein the clinical information fields comprise patient information, clinical test results, diagnoses, symptoms, genetic mutations, treatments, and/or patient outcomes (Ozeran, Fig.19, diagnosis).
As per claim 12, the system of Ozeran and Tamilarasan teaches the system of claim 4, wherein the sequential report mapping process involves prompting the user, via the graphical user interface, to indicate whether the clinical information fields are required or optional (Ozeran, para.208, 210, fields enabled if required).
As per claim 13, the system of Ozeran and Tamilarasan teaches the system of claim 4, wherein the first clinical report comprises genomics reports and at least one of the corresponding clinical information fields comprises a genetic mutation (Ozeran, Fig.41, genetic fields).
Claim 14 is similar in scope to claim 5, and is therefore rejected under similar rationale.
Claim 15 is similar in scope to claim 6, and is therefore rejected under similar rationale.
Claim 21 is similar in scope to claim 12, and is therefore rejected under similar rationale.
Claim 22 is similar in scope to claim 14, and is therefore rejected under similar rationale.
Claims 7 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Ozeran (US 2020/0335188) and Tamilarasan et al. (“Tamilarasan”, US 2017/0286388) in view of Riss et al. (“Riss”, US 2004/0103367).
As per claim 7, the system of Ozeran and Tamilarasan teaches the system of claim 5, however does not teach wherein mapping the clinical information fields to the corresponding clinical information fields comprises determining coordinates of the clinical information fields within the first clinical report. Riss teaches a system of mapping documents including determining coordinates of the fields within the report (Riss, para.188-191, 387-398, fields mapped to template with zone info). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include Riss’s teaching with the system of Ozeran and Tamilarasan in order to ensure accurate mapping (Riss, para.12).
Claim 16 is similar in scope to claim 7, and is therefore rejected under similar rationale.
Claims 8-9 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Ozeran (US 2020/0335188) and Tamilarasan et al. (“Tamilarasan”, US 2017/0286388) in view of Urbschat et al. (“Urbschat”, US 2011/0106823).
As per claim 8, the system of Ozeran and Tamilarasan teaches the system of claim 4, however does not teach wherein mapping the clinical information fields to the corresponding clinical information fields comprises determining relative positions between the corresponding clinical information fields within the first clinical report. Urbschat teaches a system of mapping documents including determining relative positions between the corresponding clinical information fields within the first clinical report (Urbschat, para.39, 43, 46, anchor word in relative position to target words). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include Urbschat’s teaching with the system of Ozeran and Tamilarasan in order to efficiently map elements from unstructured data to structured data.
As per claim 9, the system of Ozeran, Tamilarasan and Urbschat teaches the system of claim 8, wherein the data model generator is further configured to prompt the user to assign an information field as an anchor point from which each of the remaining clinical information fields is mapped (Urbschat, para.20, 37-39, 45-46, reference anchor point mapped to other targets).
Claim 17 is similar in scope to claim 8, and is therefore rejected under similar rationale.
Claim 18 is similar in scope to claim 9, and is therefore rejected under similar rationale.
Claims 10 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ozeran (US 2020/0335188) and Tamilarasan et al. (“Tamilarasan”, US 2017/0286388) in view of Huang (US 2001/0032218).
As per claim 10, the system of Ozeran and Tamilarasan teaches the system of claim 5, however does not teach wherein mapping the clinical information fields to the corresponding clinical information fields comprises determining font attributes of the information fields within the first clinical report. Huang teaches a system of generating structured documents including determining font attributes of the information fields within the report (Huang, para.42, 66-72, parsing elements with font attributes). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include Huang’s teaching with the system of Ozeran and Tamilarasan in order to keep consistent format of elements from unstructured data to structured data.
Claim 19 is similar in scope to claim 10, and is therefore rejected under similar rationale.
Claims 11 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Ozeran (US 2020/0335188) and Tamilarasan et al. (“Tamilarasan”, US 2017/0286388) in view of Wnek (US 7,149,347).
As per claim 11, the system of Ozeran and Tamilarasan teaches the system of claim 4, however does not teach wherein the clinical report data model comprises a computer-readable model compatible with all clinical reports having the same document structure as the clinical report documents. Wnek teaches a system of mapping documents wherein the data model comprises a computer-readable model compatible with all reports having the same document structure as the report documents (Wnek, col.8, lines 1-30; col.9, lines 19-34, col.12, lines 1-7, same template used for same structured documents). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include Wnek’s teaching with the system of Ozeran and Tamilarasan in order to reduce processing time and storage.
Claim 20 is similar in scope to claim 11, and is therefore rejected under similar rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Hashem et al. (US 2023/0086605) teaches a method of generating customized templates to include only needed fields.
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/S.M./
Sajeda MuhebbullahExaminer, Art Unit 2174
/WILLIAM L BASHORE/ Supervisory Patent Examiner, Art Unit 2174