AI Medical Compendium

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

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Pre-trained Maldi Transformers improve MALDI-TOF MS-based prediction.

Computers in biology and medicine
For the last decade, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been the reference method for species identification in clinical microbiology. Hampered by a historical lack of open data, machine le...

Interpretable COVID-19 chest X-ray detection based on handcrafted feature analysis and sequential neural network.

Computers in biology and medicine
Deep learning methods have significantly improved medical image analysis, particularly in detecting COVID-19 chest X-rays. Nonetheless, these methodologies frequently inhibit some drawbacks, such as limited interpretability, extensive computational r...

Guardian-BERT: Early detection of self-injury and suicidal signs with language technologies in electronic health reports.

Computers in biology and medicine
Mental health disorders, including non-suicidal self-injury (NSSI) and suicidal behavior, represent a growing global concern. Early detection of these conditions is crucial for timely intervention and prevention of adverse outcomes. In this study, we...

ATEDU-NET: An Attention-Embedded Deep Unet for multi-disease diagnosis in chest X-ray images, breast ultrasound, and retina fundus.

Computers in biology and medicine
In image segmentation for medical image analysis, effective upsampling is crucial for recovering spatial information lost during downsampling. This challenge becomes more pronounced when dealing with diverse medical image modalities, which can signif...

Automated model discovery for tensional homeostasis: Constitutive machine learning in growth and remodeling.

Computers in biology and medicine
We present a built-in physics neural network architecture, known as inelastic Constitutive Artificial Neural Network (iCANN), to discover the inelastic phenomenon of tensional homeostasis. In this course, identifying the optimal model and material pa...

PPILS: Protein-protein interaction prediction with language of biological coding.

Computers in biology and medicine
Protein-protein interactions within a cell are essential for various fundamental biological processes. Computational techniques have arisen in bioinformatics due to the challenging and resource-intensive nature of experimental protein pair interactio...

Addressing data uncertainty of Caulobacter crescentus cell cycles using hybrid Petri nets with fuzzy kinetics.

Computers in biology and medicine
Studying and analysing the various phases and key proteins of cell cycles is essential for the understanding of cell development and differentiation. To this end, mechanistic models play an important role towards a system level understanding of the i...

Synthesized colonoscopy dataset from high-fidelity virtual colon with abnormal simulation.

Computers in biology and medicine
With the advent of the deep learning-based colonoscopy system, the need for a vast amount of high-quality colonoscopy image datasets for training is crucial. However, the generalization ability of deep learning models is challenged by the limited ava...

ResViT FusionNet Model: An explainable AI-driven approach for automated grading of diabetic retinopathy in retinal images.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Diabetic Retinopathy (DR) is a serious diabetes complication that can cause blindness if not diagnosed in its early stages. Manual diagnosis by ophthalmologists is labor-intensive and time-consuming, particularly in overburd...

Optimized assessment of physical rehabilitation exercises using spatiotemporal, sequential graph-convolutional networks.

Computers in biology and medicine
Rehabilitation is the process of helping people regain or improve lost or impaired function due to injury, illness, or disease. To assist in tracking the progress of patients undergoing rehabilitation, this paper proposes a lightweight graph-based de...