AIMC Topic: Humans

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Discovering of novel umami-enhancing peptides from Flammulina filiformis: Combining virtual screening, machine learning, molecular dynamics simulations, and sensory evaluation.

Food chemistry
This research employed integrated machine learning and bioinformatics approaches to identify umami-enhancing peptides from Flammulina filiformis, elucidate their mechanisms of umami augmentation, and validate their efficacy through sensory evaluation...

Rehabilitation, neuroplasticity, and machine learning: Approaching artificial intelligence for equitable health systems.

Neuroscience
Recently, technology has evolved significantly in the rehabilitation process for neurological disorders and neurodegenerative diseases, focusing on neuroplasticity. Neuroplasticity, as a fundamental base of brain rehabilitation, is the change in the ...

Manifold Embedding of Quantum Information as Molecule Representation to Predict Blood-Brain Barrier Permeability by Deep Learning.

Molecular pharmaceutics
Neurological disorders continue to be a leading global health challenge, with the blood-brain barrier (BBB) presenting considerable obstacles to effective drug delivery for central nervous system (CNS) therapies. Accurately predicting BBB permeabilit...

Artificial Intelligence Modeling for Groundwater Environments across Spatial Scales.

Environmental science & technology
Groundwater is threatened by climate change and human activities, with depletion and contamination emerging as critical risks, necessitating the development of models to estimate its response to changes. Artificial intelligence (AI) is gaining increa...

StratoLAMP-2: A Microfluidics-Free, Deep-Learning Platform for Multiplex Digital Molecular Diagnostics.

Analytical chemistry
Accurate and accessible molecular diagnostics are critical for early disease detection, infection control, and personalized medicine. Digital nucleic acid testing offers absolute quantification by isolating individual amplification events into discre...

Centiloid values from deep learning-based CT parcellation: a valid alternative to freesurfer.

Alzheimer's research & therapy
BACKGROUND: Amyloid PET/CT is essential for quantifying amyloid-beta (Aβ) deposition in Alzheimer's disease (AD), with the Centiloid (CL) scale standardizing measurements across imaging centers. However, MRI-based CL pipelines face challenges: high c...

Screening and experimental study of potential biomarkers for ulcerative colitis based on weighted gene co-expression network analysis and machine learning.

Journal of translational medicine
BACKGROUND: Ulcerative colitis (UC) is a chronic nonspecific inflammatory intestinal disease affecting the mucosa and submucosa, characterized by continuous and diffuse active inflammation. However, its underlying pathogenesis remains unclear.

petBrain: a new pipeline for amyloid, Tau tangles and neurodegeneration quantification using PET and MRI.

Alzheimer's research & therapy
INTRODUCTION: Quantification of amyloid plaques (A), neurofibrillary tangles (T), and neurodegeneration (N) using PET and MRI is critical for Alzheimer's disease (AD) diagnosis and prognosis. Existing pipelines face limitations regarding processing t...

Deep learning-aided optical biopsy achieves whole-chain diagnosis of Correa cascade of gastric cancer: a prospective study.

BMC medicine
BACKGROUND: Biopsies are essential in differentiating benign from malignant lesions in routine gastroscopy. Nevertheless, redundant biopsies increase patients' expenses and pathologists' workload. Probe-based confocal laser endomicroscopy (pCLE) enab...

Postgraduate nursing students' knowledge, attitudes, and practices regarding artificial intelligence: a qualitative study.

BMC medical education
BACKGROUND: The combination of healthcare and artificial intelligence (AI) has profoundly changed the course of certain areas of nursing. Postgraduate nursing students, as key contributors to the discipline's development, warrant investigation regard...