AI Medical Compendium Journal:
Computers in biology and medicine

Showing 1 to 10 of 1779 articles

Artificial intelligence based malignant lymphoma type prediction using enhanced super resolution image and hybrid feature extraction algorithm.

Computers in biology and medicine
In the medical field, the most common and frequent type of blood cancer is lymphoma. Accurately predicting and early response to lymphoma treatment will be useful for initiating treatment plans to achieve a greater rate of cure or reduced risk of tre...

Radiology report generation based on adaptive enhanced fusion of multi features.

Computers in biology and medicine
The radiology report is essential for doctors' diagnosis and treatment. The automatic generation of radiology reports can assist doctors in diagnosis and treatment, thereby reducing their workload. Some existing studies consider the entire radiologic...

Time-series deep learning and conformal prediction for improved sepsis diagnosis in primarily Non-ICU hospitalized patients.

Computers in biology and medicine
PURPOSE: Sepsis, a life-threatening condition from an uncontrolled immune response to infection, is a leading cause of in-hospital mortality. Early detection is crucial, yet traditional diagnostic methods, like SIRS and SOFA, often fail to identify s...

Multimodal AI framework for lung cancer diagnosis: Integrating CNN and ANN models for imaging and clinical data analysis.

Computers in biology and medicine
Lung cancer remains a leading cause of cancer-related mortality worldwide, emphasizing the critical need for accurate and early diagnostic solutions. This study introduces a novel multimodal artificial intelligence (AI) framework that integrates Conv...

Multiclass ensemble framework for enhanced prostate gland Segmentation: Integrating Self-ONN decoders with EfficientNet.

Computers in biology and medicine
Digital pathology relies on the morphological architecture of prostate glands to recognize cancerous tissue. Prostate cancer (PCa) originates in walnut shaped prostate gland in the male reproductive system. Deep learning (DL) pipelines can assist in ...

A medical information extraction model with contrastive tuning and tagging layer training.

Computers in biology and medicine
Medical information extraction, as a core task in medical intelligent systems, focuses on extracting necessary structured information from clinical texts. In recent years, deep learning-based methods have become mainstream and often achieve superior ...

Estimation of time-to-total knee replacement surgery with multimodal modeling and artificial intelligence.

Computers in biology and medicine
BACKGROUND: The methods for predicting time-to-total knee replacement (TKR) do not provide enough information to make robust and accurate predictions.

MHS U-Net: Multi-scale hybrid subtraction network for medical image segmentation.

Computers in biology and medicine
Medical image segmentation plays a critical role in modern clinical diagnosis. However, existing methods face challenges such as insufficient feature extraction, limited spatial modeling capabilities, and restricted generalization ability with low co...

Ultra-low-power System-on-Chip for automated screening of central apnea and hypopnea via chin electromyography.

Computers in biology and medicine
Central Apnea (CA) and Central Hypopnea (CH) are sleep disorders arising from the brain's inability to signal respiratory muscles, potentially leading to severe complications such as heart failure. This study presents a novel system for automating CA...

Brain Fractal Dimension and Machine Learning can predict first-episode psychosis and risk for transition to psychosis.

Computers in biology and medicine
Although there are notable structural abnormalities in the brain associated with psychotic diseases, it is still unclear how these abnormalities relate to clinical presentation. However, the fractal dimension (FD), which offers details on the complex...