AIMC Topic: Humans

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A hybrid long short-term memory-convolutional neural network multi-stream deep learning model with Convolutional Block Attention Module incorporated for monkeypox detection.

Science progress
BackgroundMonkeypox (mpox) is a zoonotic infectious disease caused by the mpox virus and characterized by painful body lesions, fever, headaches, and exhaustion. Since the report of the first human case of mpox in Africa, there have been multiple out...

Establishing Artificial Intelligence-Powered Virtual Tumor Board Meetings in Pakistan.

Cancer control : journal of the Moffitt Cancer Center
Equitable cancer care in low- and middle-income countries is crucial as mortality rates continue to rise. Artificial intelligence (AI)-powered Virtual Tumor Board Meetings (VTBMs) offer an innovative solution that facilitates real-time collaboration ...

Deep Learning-Based Auto-Segmentation for Liver Yttrium-90 Selective Internal Radiation Therapy.

Technology in cancer research & treatment
The aim was to evaluate a deep learning-based auto-segmentation method for liver delineation in Y-90 selective internal radiation therapy (SIRT). A deep learning (DL)-based liver segmentation model using the U-Net3D architecture was built. Auto-segme...

Spanish language version of the "Medical Quality Video Evaluation Tool" (MQ-VET): Cross-cultural AI-supported adaptation and validation study.

Science progress
BACKGROUND: The Medical Quality Video Evaluation Tool (MQ-VET) is a standardized instrument for assessing health-related video quality, yet it is only available in English. This study addresses the growing demand for a Spanish version to better suppo...

Deciphering Insomnia: Benchmarking Automated Sleep Staging Algorithms for Complex Sleep Disorders.

Journal of sleep research
Polysomnography (PSG) is essential for diagnosing sleep disorders, but its manual interpretation is labor-intensive. Automated sleep staging algorithms are promising, yet their utility in complex sleep disorders such as insomnia remains uncertain. Th...

High-throughput microfluidics for precise separation and focusing of circulating tumor cells with optimized triangular microchannel design.

Talanta
The precise separation and focusing of circulating tumor cells (CTCs) from blood cells are crucial for advancing cancer diagnosis, optimizing therapeutic strategies, and fostering progress in cellular research. Inertial microfluidics offers an effici...

A Novel, Interpretable Machine Learning Model to Predict Neurological Outcomes Following Venoarterial Extracorporeal Membrane Oxygenation.

Neurocritical care
BACKGROUND: We used machine learning models incorporating rich electronic medical record (EMR) data to predict neurological outcomes after venoarterial extracorporeal membrane oxygenation (VA-ECMO).

Evaluating the value of AI-generated questions for USMLE step 1 preparation: A study using ChatGPT-3.5.

Medical teacher
PURPOSE: Students are increasingly relying on artificial intelligence (AI) for medical education and exam preparation. However, the factual accuracy and content distribution of AI-generated exam questions for self-assessment have not been systematica...

MRI-based radiomics for prediction of biochemical recurrence in prostate cancer: a systematic review and meta-analysis.

Abdominal radiology (New York)
BACKGROUND AND PURPOSE: Biochemical recurrence (BCR) following prostate cancer (PCa) treatment is a significant indicator of metastasis and mortality. Early prediction of BCR can guide treatment decisions, and optimize patient management strategies. ...

Esophageal Intelligence: Implementing Artificial Intelligence Into the Diagnostics of Esophageal Motility and Impedance pH Monitoring.

Neurogastroenterology and motility
Esophageal motility disorders (EMDs) encompass a range of functional abnormalities, including achalasia, ineffective esophageal motility (IEM), esophagogastric junction outflow obstruction (EGJOO), and distal esophageal spasm (DES). Diagnostic modali...