AIMC Topic: Humans

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Ultradense Electrochemical Chip and Machine Learning for High-Throughput, Accurate Anticancer Drug Screening.

ACS sensors
Despite the potentialities of electrochemical sensors, these devices still encounter challenges in devising high-throughput and accurate drug susceptibility testing. The lack of platforms for providing these analyses over the preclinical trials of dr...

Identification of Staphylococcus aureus, Enterococcus faecium, Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii from Raman spectra by Artificial Intelligent Raman Detection and Identification System (AIRDIS) with machine learning.

Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi
BACKGROUND: Rapid and accurate identification of bacteria is required in order to develop effective treatment strategies. Traditional culture-based methods are time-consuming, while MALDI-TOF MS is expensive. The Raman spectroscopy, due to its relati...

Using Generative Artificial Intelligence in Medical Education.

Academic medicine : journal of the Association of American Medical Colleges
Large Language Models (LLMs) are a type of generative artificial intelligence (AI) that produce realistic-sounding language in response to text prompts, giving AI the capability to simulate human discourse in various domains, including medical educat...

Reevaluating feature importances in machine learning models for schizophrenia and bipolar disorder: The need for true associations.

Brain, behavior, and immunity
Skorobogatov et al. developed supervised machine learning models to predict diagnoses and illness states in schizophrenia and bipolar disorder. However, their reliance on bootstrap forests and generalized regressions introduces significant biases in ...

Application of one-class classification using deep learning technique improves the classification of subvisible particles.

Journal of pharmaceutical sciences
Capturing subvisible particles using flow imaging microscopy is useful for evaluating protein aggregates that may induce immunogenicity. Automated labeling is desirable to distinguish harmless components such as silicone oil (SO) from subvisible part...

Enhancements in artificial intelligence for medical examinations: A leap from ChatGPT 3.5 to ChatGPT 4.0 in the FRCS trauma & orthopaedics examination.

The surgeon : journal of the Royal Colleges of Surgeons of Edinburgh and Ireland
INTRODUCTION: ChatGPT is a sophisticated AI model capable of generating human-like text based on the input it receives. ChatGPT 3.5 showed an inability to pass the FRCS (Tr&Orth) examination due to a lack of higher-order judgement in previous studies...

Rational design of potent phosphopeptide binders to endocrine Snk PBD domain by integrating machine learning optimization, molecular dynamics simulation, binding energetics rescoring, and in vitro affinity assay.

European biophysics journal : EBJ
Human Snk is an evolutionarily conserved serine/threonine kinase essential for the maintenance of endocrine stability. The protein consists of a N-terminal catalytic domain and a C-terminal polo-box domain (PBD) that determines subcellular localizati...

Assessment of clinical feasibility:offline adaptive radiotherapy for lung cancer utilizing kV iCBCT and UNet++ based deep learning model.

Journal of applied clinical medical physics
BACKGROUND: Lung cancer poses a significant global health challenge. Adaptive radiotherapy (ART) addresses uncertainties due to lung tumor dynamics. We aimed to investigate a comprehensively and systematically validated offline ART regimen with high ...

Left Atrial Wall Thickness Measured by a Machine Learning Method Predicts AF Recurrence After Pulmonary Vein Isolation.

Journal of cardiovascular electrophysiology
BACKGROUND: Left atrial (LA) remodeling plays a significant role in the progression of atrial fibrillation (AF). Although LA wall thickness (LAWT) has emerged as an indicator of structural remodeling, its impact on AF outcomes remains unclear. We aim...

Long-duration electrocardiogram classification based on Subspace Search VMD and Fourier Pooling Broad Learning System.

Medical engineering & physics
Detecting early stages of cardiovascular disease from short-duration Electrocardiogram (ECG) signals is challenging. However, long-duration ECG data are susceptible to various types of noise during acquisition. To tackle the problem, Subspace Search ...