AIMC Topic: Algorithms

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Using Machine Learning and Artificial Intelligence to Predict Diabetes Mellitus among Women Population.

Current diabetes reviews
BACKGROUND: Diabetes Mellitus is a chronic health condition (long-lasting) due to inadequate control of blood levels of glucose. This study presents a prediction of Type 2 Diabetes Mellitus among women using various Machine Learning Algorithms deploy...

ChatGPT-4.0 in oral and maxillofacial radiology: prediction of anatomical and pathological conditions from radiographic images.

Folia medica
ChatGPT has the ability to generate human-like text, analyze and understand medical images using natural Language processing (NLP) algorithms. It can generate real-time diagnosis and recognize patterns and learn from previous cases to improve accurac...

Dynamic and concordance-assisted learning for risk stratification with application to Alzheimer's disease.

Biostatistics (Oxford, England)
Dynamic prediction models capable of retaining accuracy by evolving over time could play a significant role for monitoring disease progression in clinical practice. In biomedical studies with long-term follow up, participants are often monitored thro...

BetaAlign: a deep learning approach for multiple sequence alignment.

Bioinformatics (Oxford, England)
MOTIVATION: Multiple sequence alignments (MSAs) are extensively used in biology, from phylogenetic reconstruction to structure and function prediction. Here, we suggest an out-of-the-box approach for the inference of MSAs, which relies on algorithms ...

Quantitative analysis of the dexamethasone side effect on human-derived young and aged skeletal muscle by myotube and nuclei segmentation using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Skeletal muscle cells (skMCs) combine together to create long, multi-nucleated structures called myotubes. By studying the size, length, and number of nuclei in these myotubes, we can gain a deeper understanding of skeletal muscle develop...

DPAM-AI: a domain parser for AlphaFold models powered by artificial intelligence.

Bioinformatics (Oxford, England)
MOTIVATION: Due to the breakthrough in protein structure prediction by AlphaFold, the scientific community has access to 200 million predicted protein structures with near-atomic accuracy from the AlphaFold protein structure DataBase (AFDB), covering...

[Research progress on endoscopic image diagnosis of gastric tumors based on deep learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Gastric tumors are neoplastic lesions that occur in the stomach, posing a great threat to human health. Gastric cancer represents the malignant form of gastric tumors, and early detection and treatment are crucial for patient recovery. Endoscopic exa...

[Optimization of centrifugal artificial heart pump blade parameters based on back propagation neural network and grey wolf optimization algorithm].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The impeller, as a key component of artificial heart pumps, experiences high shear stress due to its rapid rotation, which may lead to hemolysis. To enhance the hemolytic performance of artificial heart pumps and identify the optimal combination of b...

[Cardiac magnetic resonance image segmentation based on lightweight network and knowledge distillation strategy].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
To address the issue of a large number of network parameters and substantial floating-point operations in deep learning networks applied to image segmentation for cardiac magnetic resonance imaging (MRI), this paper proposes a lightweight dilated par...

[Coronary artery segmentation based on Transformer and convolutional neural networks dual parallel branch encoder neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Manual segmentation of coronary arteries in computed tomography angiography (CTA) images is inefficient, and existing deep learning segmentation models often exhibit low accuracy on coronary artery images. Inspired by the Transformer architecture, th...