Machine Learning Algorithm in Predicting Non-Diabetic Kidney Disease in Type 2 Diabetes Mellitus: Development and Validation of a Noninvasive Predictor Scoring Modeldoi:10.1681/ASN.20233411S192bVamsidhar VeerankiNarayan PrasadJeyakumar Meyyappan
We show that the machine learning model performs well in identifying patients with cardiac amyloidosis in the derivation cohort and all four validation cohorts, thereby providing a systematic framework to increase the suspicion of transthyretin cardiac amyloidosis in patients with heart failure....
K-Means ClusteringHierarchical ClusteringExpectation and Maximization AlgorithmGrid Based CalculationClustering or group examination can be considered as a key unit in information investigation, whose primary point is to isolate the information, informational iGoyal, YogitaGoyal, YojanaSharma, Anand...
Through the results, machine learning methods showed competence in predicting risk of T2DM, leading to greater insights on disease risk factors with no priori assumption of causality.Similar content being viewed by others An enhanced machine learning algorithm for type 2 diabetes prognosis with a ...
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The aim of this paper is to discuss the class of leap-frog-type neural learning algorithms having the unitary group of matrices as parameter space. In the discussed framework, each step of a learning algorithm computes as an unconstrained learning step followed by a projection step. The present...
Adding Typescript implementation of the tiktoken algorithm. (#8) May 12, 2023 CODE_OF_CONDUCT.md CODE_OF_CONDUCT.md committed Mar 28, 2023 CONTRIBUTING.md docs: update CONTRIBUTING.md (#51) Jul 19, 2024 LICENSE LICENSE committed Mar 28, 2023 ...
(Fixed-Point Designer). Then use the lookup table for fixed-point code generation. This approach requires fewer calculations for score transformation in the generated code than the default approach, which uses the CORDIC-based algorithm. Therefore, using a lookup table yields relatively high-speed ...
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(Fig.3e,f). The results showed that patients who received doses similar to the doses recommended by the AI algorithm can typically achieve desired glucose control, both in the internal set (interquartile range, −2 to 0 U) and the external test set (interquartile range, 0–1 U)...