AI Medical Compendium

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

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A machine learning based death risk analysis and prediction of ST-segment elevation myocardial infarction (STEMI) patients.

Computers in biology and medicine
Acute myocardial infarction is a condition in which a part of the heart muscle cannot receive enough blood due to the narrowing and blockage of the vessels feeding the heart over time. Noticing this situation lately and failing to intervene immediate...

Artificial Intuition and accelerating the process of antimicrobial drug discovery.

Computers in biology and medicine
New drug development is a very challenging, expensive, and usually time-consuming process. This issue is very important with regard to antimicrobials, which are affected by the global issue of the development and spread of resistance. This framework ...

PhageDPO: A machine-learning based computational framework for identifying phage depolymerases.

Computers in biology and medicine
Bacteriophages (phages) are the most predominant and genetically diverse biological entities on Earth. Phages are viruses that infect bacteria and encode numerous proteins with potential biotechnological application. However, most phage-encoded prote...

Detection of brain tumors using a transfer learning-based optimized ResNet152 model in MR images.

Computers in biology and medicine
Brain tumors are incredibly harmful and can drastically reduce life expectancy. Most researchers use magnetic resonance (MR) scans to detect tumors because they can provide detailed images of the affected area. Recently, AI-based deep learning method...

Active learning and margin strategies for arrhythmia classification in implantable devices.

Computers in biology and medicine
BACKGROUND AND OBJECTIVES: The massive storage of cardiac arrhythmic episodes from Implantable Cardioverter Defibrillators (ICD) and the advent of new artificial intelligence algorithms are opening up new opportunities for electrophysiological knowle...

EAMAPG: Explainable Adversarial Model Analysis via Projected Gradient Descent.

Computers in biology and medicine
Despite the outstanding performance of deep learning (DL) models, their interpretability remains a challenging topic. In this study, we address the transparency of DL models in medical image analysis by introducing a novel interpretability method usi...

X-scPAE: An explainable deep learning model for embryonic lineage allocation prediction based on single-cell transcriptomics revealing key genes in embryonic cell development.

Computers in biology and medicine
In single-cell transcriptomics research, accurately predicting cell lineage allocation and identifying differences between lineages are crucial for understanding cell differentiation processes and reducing early pregnancy miscarriages in humans. This...

Real-time adaptive proton therapy: An AI-based spatio-temporal mono-energetic dose calculation model (CC-LSTM).

Computers in biology and medicine
PURPOSE: To develop a fully AI-based dose estimation model capable of learning and estimating single pencil beam dose distributions, and to verify its performance by testing the model's generalizability on unseen, previously delivered treatment plans...

Gabor-modulated depth separable convolution for retinal vessel segmentation in fundus images.

Computers in biology and medicine
BACKGROUND: In diabetic retinopathy, precise segmentation of retinal vessels is essential for accurate diagnosis and effective disease management. This task is particularly challenging due to the varying sizes of vessels, their bifurcations, and the ...

Multitask learning approach for PPG applications: Case studies on signal quality assessment and physiological parameters estimation.

Computers in biology and medicine
Wearable technology has expanded the applications of photoplethysmography (PPG) in remote health monitoring, enabling real-time measurement of various physiological parameters, such as heart rate (HR), heart rate variability (HRV), and respiration ra...