AIMC Topic: Humans

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Hybrid Anomaly Detection in Time Series by Combining Kalman Filters and Machine Learning Models.

Sensors (Basel, Switzerland)
Due to connectivity and automation trends, the medical device industry is experiencing increased demand for safety and security mechanisms. Anomaly detection has proven to be a valuable approach for ensuring safety and security in other industries, s...

QTNet: Predicting Drug-Induced QT Prolongation With Artificial Intelligence-Enabled Electrocardiograms.

JACC. Clinical electrophysiology
BACKGROUND: Prediction of drug-induced long QT syndrome (diLQTS) is of critical importance given its association with torsades de pointes. There is no reliable method for the outpatient prediction of diLQTS.

Identifying lncRNAs and mRNAs related to survival of NSCLC based on bioinformatic analysis and machine learning.

Aging
Non-small cell lung cancer (NSCLC) is the most common histopathological type, and it is purposeful for screening potential prognostic biomarkers for NSCLC. This study aims to identify the lncRNAs and mRNAs related to survival of non-small cell lung c...

Community screening for dementia among older adults in China: a machine learning-based strategy.

BMC public health
BACKGROUND: Dementia is a leading cause of disability in people older than 65 years worldwide. However, diagnosing dementia in its earliest symptomatic stages remains challenging. This study combined specific questions from the AD8 scale with compreh...

Reactivities of acrylamide warheads toward cysteine targets: a QM/ML approach to covalent inhibitor design.

Journal of computer-aided molecular design
Covalent inhibition offers many advantages over non-covalent inhibition, but covalent warhead reactivity must be carefully balanced to maintain potency while avoiding unwanted side effects. While warhead reactivities are commonly measured with assays...

An artificial visual neuron with multiplexed rate and time-to-first-spike coding.

Nature communications
Human visual neurons rely on event-driven, energy-efficient spikes for communication, while silicon image sensors do not. The energy-budget mismatch between biological systems and machine vision technology has inspired the development of artificial v...