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 Objections
Claim 1 is objected to because of the following informalities: The claims reads “based an artificial intelligence…” Examiner believes “an” should be “on.” Appropriate correction is required.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 4-7, 11, and 14-17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Application Publication No 2021/211516 granted to Kumar.
In reference to claims 1 and 11, Kumar discloses an apparatus and method for predicting re-rupture of a tendon based an artificial intelligence [e.g. paragraph 0061], the apparatus comprising: a communication module configured to make communication with an external device [e.g. paragraph 0069]; an acquiring module configured to acquire at least one arthroscopic image including a surgical portion of a patient experiencing a surgery [e.g. paragraph 0078]; a storage module configured to store at least one process based on the AI [e.g. paragraph 0081]; a control module [e.g. CPU 106] configured to perform an operation for predicting the re-rupture of the tendon based on the AI, through the at least one process [e.g. paragraphs 0004, 0082], and wherein the control module is configured to: perform a pre-processing operation for the at least one arthroscopic image, predict a probability of the re-rupture of the tendon by inputting the at least one arthroscopic image, which is pre-processed, into a pre-trained model based on the AI, and generate prediction information for the patient based on a prediction result [e.g. paragraphs 0004, 0082].
In reference to claims 4 and 14, Kumar discloses wherein the training module classifies, manages, and uses the plurality of arthroscopic images into a first group for a patient having no re-rupture and a second group having re-rupture [e.g. paragraph 0046 (it is understood by examiner that since Kumar classifies the images, grouping them is inherent)].
In reference to claims 5 and 15, Kumar discloses wherein the training module specifies at least one region in each of the plurality of arthroscopic images when pre-processing the plurality of arthroscopic images, and labels at least one of whether the at least one region specified is re-ruptured or a time point at which the at least one region specified is re-ruptured [e.g. paragraph 0046].
In reference to claims 6 and 16, Kumar discloses wherein the prediction information includes: a region to be predicted to be re-ruptured with respect to the patient, a tendon state for each region, a probability of the re-rupture, and timing predicted to be re-ruptured [e.g. paragraph 0046].
In reference to claims 7 and 17, Kumar discloses wherein the control module performs a categorizing operation depending on the probability of the re-rupture of the patient [e.g. paragraphs 0004, 0082].
Allowable Subject Matter
Claims 2 and 12 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. The claims differ from the closest prior art of Kumar since the claims recited collecting and pre-processing a plurality of arthroscopic images for each of different patients, whereas Kumar is limited to a single patient.
Claims 3 and 13 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. The claims differ from the closest prior art of Kumar, since the claims recite images being collected at different time points for a preset period, whereas Kumar collects images in real time.
Claims 8 and 18 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. The claims differ from the closest prior art of Kumar, since the claims require the training to be performed in a preset number of times using RMSProp. Kumar does not disclose such feature.
Claims 9 and 19 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. The claims differ from the closest prior art of Kumar, since the claims require the use of predictive accuracy, F1score, AUC sensitivity. Kumar does not disclose such features.
Claims 10 and 20 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. The claims differ from the closest prior art of Kumar, since the claims require equations to calculate the predictive accuracy and J statistics to calculate a threshold value. Kumar does not disclose such features.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NADIA AHMAD MAHMOOD whose telephone number is (571)270-3975. The examiner can normally be reached Monday-Friday 8am-4pm.
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/NADIA A MAHMOOD/Primary Examiner, Art Unit 3796
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