AIMC Topic: Humans

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Construction of a prediction model for drug removal rate in hemodialysis based on chemical structures.

Molecular diversity
In designing drug dosing for hemodialysis patients, the removal rate (RR) of the drug by hemodialysis is important. However, acquiring the RR is difficult, and there is a need for an estimation method that can be used in clinical settings. In this st...

Diagnostic effect of artificial intelligence solution for referable thoracic abnormalities on chest radiography: a multicenter respiratory outpatient diagnostic cohort study.

European radiology
OBJECTIVES: We aim ed to evaluate a commercial artificial intelligence (AI) solution on a multicenter cohort of chest radiographs and to compare physicians' ability to detect and localize referable thoracic abnormalities with and without AI assistanc...

Overview on prediction, detection, and classification of atrial fibrillation using wavelets and AI on ECG.

Computers in biology and medicine
Atrial fibrillation (AF) is the most common supraventricular cardiac arrhythmia, resulting in high mortality rates among affected patients. AF occurs as episodes coming from irregular excitations of the ventricles that affect the functionality of the...

Human Activity Recognition via Hybrid Deep Learning Based Model.

Sensors (Basel, Switzerland)
In recent years, Human Activity Recognition (HAR) has become one of the most important research topics in the domains of health and human-machine interaction. Many Artificial intelligence-based models are developed for activity recognition; however, ...

A Remote Calibration Device Using Edge Intelligence.

Sensors (Basel, Switzerland)
Power system facility calibration is a compulsory task that requires in-site operations. In this work, we propose a remote calibration device that incorporates edge intelligence so that the required calibration can be accomplished with little human i...

Integrated Machine Learning and Bioinformatic Analyses Constructed a Novel Stemness-Related Classifier to Predict Prognosis and Immunotherapy Responses for Hepatocellular Carcinoma Patients.

International journal of biological sciences
Immunotherapy has made great progress in hepatocellular carcinoma (HCC), yet there is still a lack of biomarkers for predicting response to it. Cancer stem cells (CSCs) are the primary cause of the tumorigenesis, metastasis, and multi-drug resistance...

What is morally at stake when using algorithms to make medical diagnoses? Expanding the discussion beyond risks and harms.

Theoretical medicine and bioethics
In this paper, we examine the qualitative moral impact of machine learning-based clinical decision support systems in the process of medical diagnosis. To date, discussions about machine learning in this context have focused on problems that can be m...

Using Machine Learning to Develop a Short-Form Measure Assessing 5 Functions in Patients With Stroke.

Archives of physical medicine and rehabilitation
OBJECTIVE: This study aimed to develop and validate a machine learning-based short measure to assess 5 functions (the ML-5F) (activities of daily living [ADL], balance, upper extremity [UE] and lower extremity [LE] motor function, and mobility) in pa...

An artificial intelligence-accelerated 2-minute multi-shot echo planar imaging protocol for comprehensive high-quality clinical brain imaging.

Magnetic resonance in medicine
PURPOSE: We introduce and validate an artificial intelligence (AI)-accelerated multi-shot echo-planar imaging (msEPI)-based method that provides T1w, T2w, , T2-FLAIR, and DWI images with high SNR, high tissue contrast, low specific absorption rates ...