AIMC Topic: Machine Learning

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Deep Learning-Based Assessment Model for Real-Time Identification of Visual Learners Using Raw EEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Automatic identification of visual learning style in real time using raw electroencephalogram (EEG) is challenging. In this work, inspired by the powerful abilities of deep learning techniques, deep learning-based models are proposed to learn high-le...

Novel graph-based machine-learning technique for viral infectious diseases: application to influenza and hepatitis diseases.

Annals of medicine
BACKGROUND: Most infectious diseases are caused by viruses, fungi, bacteria and parasites. Their ability to easily infect humans and trigger large-scale epidemics makes them a public health concern. Methods for early detection of these diseases have ...

Understanding the Pathophysiology of Mental Diseases and Early Diagnosis Thanks to Electrophysiological Tools: Some Insights and Empirical Facts.

Clinical EEG and neuroscience
. Neurophysiological tools remain indispensable instruments in the assessment of psychiatric disorders. These techniques are widely available, inexpensive and well tolerated, providing access to the assessment of brain functional alterations. In the ...

Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions.

Conservation biology : the journal of the Society for Conservation Biology
Ecosystem state transitions can be ecologically devastating or be a restoration success. State transitions are common within aquatic systems worldwide, especially considering human-mediated changes to land use and water use. We created a transferable...

Bioinformatics and Machine Learning Methods Identified MGST1 and QPCT as Novel Biomarkers for Severe Acute Pancreatitis.

Molecular biotechnology
Severe acute pancreatitis (SAP) is a life-threatening gastrointestinal emergency. The study aimed to identify biomarkers and investigate molecular mechanisms of SAP. The GSE194331 dataset from GEO database was analyzed using bioinformatics. Different...

Identification of Co-diagnostic Genes for Heart Failure and Hepatocellular Carcinoma Through WGCNA and Machine Learning Algorithms.

Molecular biotechnology
This research delves into the intricate relationship between hepatocellular carcinoma (HCC) and heart failure (HF) by exploring shared genetic characteristics and molecular processes. Employing advanced methodologies such as differential analysis, we...

Point-of-care diagnosis of tissue fibrosis: a review of advances in vibrational spectroscopy with machine learning.

Pathology
Histopathology is the gold standard for diagnosing fibrosis, but its routine use is constrained by the need for additional stains, time, personnel and resources. Vibrational spectroscopy is a novel technique that offers an alternative atraumatic appr...

ChatGPT in the Material Design: Selected Case Studies to Assess the Potential of ChatGPT.

Journal of chemical information and modeling
The pursuit of designing smart and functional materials is of paramount importance across various domains, such as material science, engineering, chemical technology, electronics, biomedicine, energy, and numerous others. Consequently, researchers ar...

Augmented drug combination dataset to improve the performance of machine learning models predicting synergistic anticancer effects.

Scientific reports
Combination therapy has gained popularity in cancer treatment as it enhances the treatment efficacy and overcomes drug resistance. Although machine learning (ML) techniques have become an indispensable tool for discovering new drug combinations, the ...

Systematic reviews of machine learning in healthcare: a literature review.

Expert review of pharmacoeconomics & outcomes research
INTRODUCTION: The increasing availability of data and computing power has made machine learning (ML) a viable approach to faster, more efficient healthcare delivery.