AIMC Topic: Humans

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Prediction of Transcription Factor Binding Sites on Cell-Free DNA Based on Deep Learning.

Journal of chemical information and modeling
Transcription factors (TFs) are important regulatory elements for vital cellular activities, and the identification of transcription factor binding sites (TFBS) can help to explore gene regulatory mechanisms. Research studies have proved that cfDNA (...

Can Generative AI improve social science?

Proceedings of the National Academy of Sciences of the United States of America
Generative AI that can produce realistic text, images, and other human-like outputs is currently transforming many different industries. Yet it is not yet known how such tools might influence social science research. I argue Generative AI has the pot...

Human Activity Recognition Algorithm with Physiological and Inertial Signals Fusion: Photoplethysmography, Electrodermal Activity, and Accelerometry.

Sensors (Basel, Switzerland)
Inertial signals are the most widely used signals in human activity recognition (HAR) applications, and extensive research has been performed on developing HAR classifiers using accelerometer and gyroscope data. This study aimed to investigate the po...

A Review of Artificial Intelligence in Breast Imaging.

Tomography (Ann Arbor, Mich.)
With the increasing dominance of artificial intelligence (AI) techniques, the important prospects for their application have extended to various medical fields, including domains such as in vitro diagnosis, intelligent rehabilitation, medical imaging...

Early identification of macrophage activation syndrome secondary to systemic lupus erythematosus with machine learning.

Arthritis research & therapy
OBJECTIVE: The macrophage activation syndrome (MAS) secondary to systemic lupus erythematosus (SLE) is a severe and life-threatening complication. Early diagnosis of MAS is particularly challenging. In this study, machine learning models and diagnost...

ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences.

Microbiome
BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identific...

Exploration of a machine learning approach for diagnosing sarcopenia among Chinese community-dwelling older adults using sEMG-based data.

Journal of neuroengineering and rehabilitation
BACKGROUND: In the practical application of sarcopenia screening, there is a need for faster, time-saving, and community-friendly detection methods. The primary purpose of this study was to perform sarcopenia screening in community-dwelling older adu...

Exploring clinical specialists' perspectives on the future role of AI: evaluating replacement perceptions, benefits, and drawbacks.

BMC health services research
BACKGROUND OF STUDY: Over the past few decades, the utilization of Artificial Intelligence (AI) has surged in popularity, and its application in the medical field is witnessing a global increase. Nevertheless, the implementation of AI-based healthcar...

Prediction of anticancer drug sensitivity using an interpretable model guided by deep learning.

BMC bioinformatics
BACKGROUND: The prediction of drug sensitivity plays a crucial role in improving the therapeutic effect of drugs. However, testing the effectiveness of drugs is challenging due to the complex mechanism of drug reactions and the lack of interpretabili...