Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 2,541 to 2,550 of 167,235 articles

Prediction of protein-protein interaction based on interaction-specific learning and hierarchical information.

BMC biology
BACKGROUND: Prediction of protein-protein interactions (PPIs) is fundamental for identifying drug targets and understanding cellular processes. The rapid growth of PPI studies necessitates the development of efficient and accurate tools for automated... read more 

Aptamer-Mediated Artificial Synapses for Neuromorphic Modulation of Inflammatory Signaling via Organic Electrochemical Transistor.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Artificial synaptic devices that mimic neuromorphic signal processing hold great promise for bioelectronic interfaces. However, most systems remain limited to physical stimuli or electroactive small molecules, lacking the ability to transduce biologi... read more 

Exhaled gas biomarkers: a non-invasive approach for distinguishing diabetes and its complications.

The Analyst
Exhaled gas detection offers a safe, convenient, and non-invasive clinical diagnostic method for preventing the progression of diabetes to complications. In this study, gas chromatography-mass spectrometry (GC-MS) analysis and statistical methods wer... read more 

Resilience as a mediator in the relationship between ambidextrous leadership and nurses' positive attitudes towards artificial intelligence.

BMC nursing
BACKGROUND: Leadership plays a pivotal role in adopting new trends within the nursing domain. Yet, the impact of ambidextrous leadership on nurses' positive attitudes towards artificial intelligence is not well understood. Furthermore, the underlying... read more 

An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders.

BMC psychiatry
BACKGROUND: Niacin Skin-Flushing Response (NSR) has emerged as a promising objective biomarker for the precise diagnosis of mental disorders. However, its diagnostic potential has been constrained by the limitations of traditional statistical approac... read more 

Colorimetric detection of bisphenol A in water: a smartphone-based sensor using inverse opal molecularly imprinted photonic crystal hydrogel.

The Analyst
Molecularly imprinted photonic crystal hydrogel (MIPCH) serves as a highly effective platform for the sensitive and selective detection of various analyte molecules. In this study, we present a smartphone-based inverse opal MIPCH (IOMIPCH) sensor des... read more 

Artificial intelligence in orthopedics: fundamentals, current applications, and future perspectives.

Military Medical Research
Conventional diagnostic and therapeutic approaches in orthopedics are frequently time intensive and associated with elevated rates of diagnostic error, underscoring the urgent need for more efficient tools to improve the current situation. Recently, ... read more 

Diagnostic Performance of Imaging-Based Artificial Intelligence Models for Preoperative Detection of Cervical Lymph Node Metastasis in Clinically Node-Negative Papillary Thyroid Carcinoma: A Systematic Review and Meta-Analysis.

Head & neck
PURPOSE: This systematic review and meta-analysis evaluated the performance of imaging-based artificial intelligence (AI) models in diagnosing preoperative cervical lymph node metastasis (LNM) in clinically node-negative (cN0) papillary thyroid carci... read more 

Enhanced gastrocnemius-mimicking lower limb powered exoskeleton robot.

Journal of neuroengineering and rehabilitation
BACKGROUND: Lower limb muscle bionic devices have attracted significant attention in rehabilitation and assistive sports technology. Despite advancements in mimicking human movement, current devices still face challenges in enhancing strength and mov... read more 

Machine learning of whole-brain resting-state fMRI signatures for individualized grading of frontal gliomas.

Cancer imaging : the official publication of the International Cancer Imaging Society
PURPOSE: Accurate preoperative grading of gliomas is critical for therapeutic planning and prognostic evaluation. We developed a noninvasive machine learning model leveraging whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) b... read more