AIMC Topic: Machine Learning

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Impact of Inflammation After Cardiac Surgery on 30-Day Mortality and Machine Learning Risk Prediction.

Journal of cardiothoracic and vascular anesthesia
OBJECTIVES: To investigate the impact of systemic inflammatory response syndrome (SIRS) on 30-day mortality following cardiac surgery and develop a machine learning model to predict SIRS.

Modeling the fasting blood glucose response to basal insulin adjustment in type 2 diabetes: An explainable machine learning approach on real-world data.

International journal of medical informatics
INTRODUCTION: Optimal basal insulin titration for people with type 2 diabetes is vital to effectively reducing the risk of complications. However, a sizeable proportion of people (30-50 %) remain in suboptimal glycemic control six months post-initiat...

Transferable automatic hematological cell classification: Overcoming data limitations with self-supervised learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Classification of peripheral blood and bone marrow cells is critical in the diagnosis and monitoring of hematological disorders. The development of robust and reliable automatic classification systems is hampered by data sca...

FedMEKT: Distillation-based embedding knowledge transfer for multimodal federated learning.

Neural networks : the official journal of the International Neural Network Society
Federated learning (FL) enables a decentralized machine learning paradigm for multiple clients to collaboratively train a generalized global model without sharing their private data. Most existing works have focused on designing FL systems for unimod...

A systematic review on the impact of artificial intelligence on electrocardiograms in cardiology.

International journal of medical informatics
BACKGROUND: Artificial intelligence (AI) has revolutionized numerous industries, enhancing efficiency, scalability, and insight generation. In cardiology, particularly through electrocardiogram (ECG) analysis, AI has the potential to improve diagnost...

Does road environment aesthetics influence risky driving behavior of autonomous vehicles? An evaluation on road readiness using explainable machine learning and random parameters multinomial logit with heterogeneity.

Accident; analysis and prevention
Aesthetics has always been an advanced requirement in road environment design, because it can provide a pleasant driving experience and guide better driving behavior for human drivers. However, it remains unknown whether aesthetics-based road environ...

A Graph-Based Machine-Learning Approach Combined with Optical Measurements to Understand Beating Dynamics of Cardiomyocytes.

Journal of computational biology : a journal of computational molecular cell biology
The development of computational models for the prediction of cardiac cellular dynamics remains a challenge due to the lack of first-principled mathematical models. We develop a novel machine-learning approach hybridizing physics simulation and graph...

Advancing brain tumor classification: A robust framework using EfficientNetV2 transfer learning and statistical analysis.

Computers in biology and medicine
Brain tumors are a significant health risk threatening humanity, and they seem to be unique challenges due to their critical location and the complexity of accurate diagnosis and treatment planning. Accurate and timely diagnosis and appropriate treat...

ECLStat: A robust machine learning based visual imaging tool for electrochemiluminescence biosensing.

Computers in biology and medicine
Visual electrochemiluminescence (ECL) has emerged as a prominent diagnostic method for accurately quantifying various disease markers even at point of care setting with high sensitivity and accuracy. It does not employ complicated instruments such as...

FertilitY Predictor-a machine learning-based web tool for the prediction of assisted reproduction outcomes in men with Y chromosome microdeletions.

Journal of assisted reproduction and genetics
PURPOSE: Y chromosome microdeletions (YCMD) are a common cause of azoospermia and oligozoospermia in men. Herein, we developed a machine learning-based web tool to predict sperm retrieval rates and success rates of assisted reproduction (ART) in men ...