AI Medical Compendium

Robust neural network-based unfolding of bremsstrahlung spectra from depth dose measurements in radiotherapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) May 13, 2026

In radiotherapy, quality control of medical linear accelerators mainly relies on absolute dose and depth dose measurements in water phantoms, while the bremsstrahlung spectrum is not routinely monitored. However, accurate knowledge of this spectrum i... read more

Comparative analysis of traditional and deep learning time series architectures for influenza A infectious disease forecasting.

Computers in biology and medicine May 13, 2026

Influenza A remains a major cause of respiratory mortality worldwide, motivating accurate forecasting to support timely preparedness and resource allocation. This study presents a comparative evaluation of two traditional seasonal time series baselin... read more

Hemovigilance in a Brazilian Amazon blood center: A temporal analysis of 5-year consumption patterns.

Hematology, transfusion and cell therapy May 13, 2026

BACKGROUND: The transfusion of blood components remains a cornerstone in the management of hematological and onco-hematological diseases. Effective blood bank management, combined with the development of predictive models for component utilization, i... read more

Ethical Responsibility in the Off-Label Use of AI in Medical Imaging.

The Journal of clinical ethics May 13, 2026

AbstractArtificial intelligence in medical imaging (AI-MI), categorized by the U.S. Food and Drug Administration (FDA) as "Software as a Medical Device," can offer significant benefit to medical care. FDA approval-represented by a "label"-indicates t... read more

An interpretable multi-task learning model for effluent quality and greenhouse gas emissions prediction in wastewater treatment plants.

Water research May 13, 2026

Wastewater treatment plants (WWTPs) face growing pressure to comply with regulatory effluent standards while reducing greenhouse gas (GHG) emissions as part of the net-zero and sustainable transformation. Recent advances in deep learning have improve... read more

Modeling Alzheimer's disease with human multi-omics profiles: Promise to personalized medicine.

Current opinion in neurobiology May 13, 2026

Alzheimer's disease (AD) presents considerable heterogeneity in disease risk and outcomes, posing a major challenge for effective therapeutic development. Recent advances in multi-omics profiling are revolutionizing our understanding of the complex A... read more

Global patterns of air pollution-attributable neonatal preterm birth mortality rates: a machine learning analysis using LSTM autoencoder and K-means clustering.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering May 13, 2026

Neonatal preterm birth is a leading cause of neonatal mortality worldwide, and maternal exposure to air pollution is increasingly recognized as a contributing factor. Quantifying the global burden of deaths attributable to air pollution is essential ... read more

The Integration of Artificial Intelligence in Radiation Medical Physics: Insights from an International Survey with Regional Variability.

Journal of radiological protection : official journal of the Society for Radiological Protection May 13, 2026

BACKGROUND: Artificial intelligence (AI) is considered to be a leading technology in radiation medical physics, which has the potential for improving efficiency and precision in imaging, radiotherapy, and nuclear medicine. Nonetheless, its applicatio... read more

Deep learning-based intraluminal gas modeling for anatomically accurate synthetic CT in MRI-based radiation therapy.

Biomedical physics & engineering express May 13, 2026

Stochastic bowel and rectal gas complicates MRI/CT deformable image registration (DIR) for synthetic CT (sCT) generation, requiring manual corrections. We propose a DIR-free, two-stage deep learning framework to improve intraluminal gas definition in... read more

Wearable Sensors for Monitoring Neurogenic Dysphagia: A Scoping Review.

Progress in biomedical engineering (Bristol, England) May 13, 2026

Neurological disorders, such as Parkinson's disease and stroke, often lead to neurogenic dysphagia, a swallowing disorder that compromises nutrition and increases the risk of malnutrition, aspiration of food, and even death. Although instrumental ass... read more

Artificial Intelligence Medical Compendium