AIMC Topic: Machine Learning

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Sensors (Basel, Switzerland)
The field of Medicine and Healthcare has attained revolutionary advancements in the last forty years. Within this period, the actual reasons behind numerous diseases were unveiled, novel diagnostic methods were designed, and new medicines were develo...

Machine Learning Analysis of Longevity-Associated Gene Expression Landscapes in Mammals.

International journal of molecular sciences
One of the important questions in aging research is how differences in transcriptomics are associated with the longevity of various species. Unfortunately, at the level of individual genes, the links between expression in different organs and maximum...

Cognitive and MRI trajectories for prediction of Alzheimer's disease.

Scientific reports
The concept of Mild Cognitive Impairment (MCI) is used to describe the early stages of Alzheimer's disease (AD), and identification and treatment before further decline is an important clinical task. We selected longitudinal data from the ADNI databa...

Qualitative and Quantitative MRI Analysis in IDH1 Genotype Prediction of Lower-Grade Gliomas: A Machine Learning Approach.

BioMed research international
PURPOSE: Preoperative prediction of isocitrate dehydrogenase 1 (IDH1) mutation in lower-grade gliomas (LGGs) is crucial for clinical decision-making. This study aimed to examine the predictive value of a machine learning approach using qualitative an...

Secure and Robust Machine Learning for Healthcare: A Survey.

IEEE reviews in biomedical engineering
Recent years have witnessed widespread adoption of machine learning (ML)/deep learning (DL) techniques due to their superior performance for a variety of healthcare applications ranging from the prediction of cardiac arrest from one-dimensional heart...

Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review.

IEEE reviews in biomedical engineering
With the advancement in artificial intelligence (AI) and machine learning (ML) techniques, researchers are striving towards employing these techniques for advancing clinical practice. One of the key objectives in healthcare is the early detection and...

Machine Learning for Clinical Outcome Prediction.

IEEE reviews in biomedical engineering
Clinical decision-making in healthcare is already being influenced by predictions or recommendations made by data-driven machines. Numerous machine learning applications have appeared in the latest clinical literature, especially for outcome predicti...

Recent Advancements and Future Prospects on E-Nose Sensors Technology and Machine Learning Approaches for Non-Invasive Diabetes Diagnosis: A Review.

IEEE reviews in biomedical engineering
Diabetes mellitus, commonly measured through an invasive process which although is accurate, has manifold drawbacks especially when multiple reading are required at regular intervals. Accordingly, there is a need to develop a dependable non-invasive ...

A Review on the State of the Art in Atrial Fibrillation Detection Enabled by Machine Learning.

IEEE reviews in biomedical engineering
Atrial Fibrillation (AF) the most commonly occurring type of cardiac arrhythmia is one of the main causesĀ of morbidity and mortality worldwide. The timely diagnosis of AF is an equally important and challenging task because of its asymptomatic and ep...

A Review on Machine Learning for EEG Signal Processing in Bioengineering.

IEEE reviews in biomedical engineering
Electroencephalography (EEG) has been a staple method for identifying certain health conditions in patients since its discovery. Due to the many different types of classifiers available to use, the analysis methods are also equally numerous. In this ...