AIMC Topic: Humans

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LW-CTrans: A lightweight hybrid network of CNN and Transformer for 3D medical image segmentation.

Medical image analysis
Recent models based on convolutional neural network (CNN) and Transformer have achieved the promising performance for 3D medical image segmentation. However, these methods cannot segment small targets well even when equipping large parameters. Theref...

Revolutionizing biological digital twins: Integrating internet of bio-nano things, convolutional neural networks, and federated learning.

Computers in biology and medicine
Digital twins (DTs) are advancing biotechnology by providing digital models for drug discovery, digital health applications, and biological assets, including microorganisms. However, the hypothesis posits that implementing micro- and nanoscale DTs, e...

Utility of comprehensive genomic profiling combined with machine learning for prognostic stratification in stage II/III colorectal cancer after adjuvant chemotherapy.

International journal of clinical oncology
BACKGROUND AND PURPOSE: Accurate recurrence risk evaluation in patients with stage II and III colorectal cancer (CRC) remains difficult. Traditional histopathological methods frequently fall short in predicting outcomes after adjuvant chemotherapy. T...

Development of a Disease Model for Predicting Postoperative Delirium Using Combined Blood Biomarkers.

Annals of clinical and translational neurology
OBJECTIVE: Postoperative delirium, a common neurocognitive complication after surgery and anesthesia, requires early detection for potential intervention. Herein, we constructed a multidimensional postoperative delirium risk-prediction model incorpor...

Accelerated intracranial time-of-flight MR angiography with image-based deep learning image enhancement reduces scan times and improves image quality at 3-T and 1.5-T.

Neuroradiology
PURPOSE: Three-dimensional time-of-flight magnetic resonance angiography (TOF-MRA) is effective for cerebrovascular disease assessment, but clinical application is limited by long scan times and low spatial resolution. Recent advances in deep learnin...

Proteomic Learning of Gamma-Aminobutyric Acid (GABA) Receptor-Mediated Anesthesia.

Journal of chemical information and modeling
Anesthetics are crucial in surgical procedures and therapeutic interventions, but they come with side effects and varying levels of effectiveness, calling for novel anesthetic agents that offer more precise and controllable effects. Targeting Gamma-a...

Artificial intelligence: A key fulcrum for addressing complex environmental health issues.

Environment international
Environmental health (EH) is a complex and interdisciplinary field dedicated to the examination of environmental behaviours, toxicological effects, health risks, and strategies for mitigating harmful environmental factors. Traditional EH research inv...

Artificial intelligence in anti-obesity drug discovery: unlocking next-generation therapeutics.

Drug discovery today
Obesity, a multifactorial disease linked to severe health risks, requires innovative treatments beyond lifestyle changes and current medications. Existing anti-obesity drugs face limitations regarding efficacy, side effects, weight regain and high co...

Reduction of Acquisition Time in Fourier Transform Infrared Spectral Imaging by Deep Learning for Clinical Applications.

Analytical chemistry
In infrared Fourier transform spectral imaging applied to biomedical challenges, data quality is of primary importance to achieving clinical objectives. However, different noise sources affect the infrared signal coming from the sample. Generally, th...

Leveraging Artificial Intelligence as a Safety Net for Incidentally Identified Lung Nodules at a Tertiary Center.

Journal of the American College of Surgeons
BACKGROUND: Artificial intelligence (AI)-powered platforms may be used to ensure that clinically significant lung nodules receive appropriate management. We studied the impact of a commercially available AI natural language processing tool on the det...