AI Medical Compendium

Composite Heat Wave Risk (CHWR) framework using Principal Component Analysis (PCA) and machine learning for assessing agro community resilience.

Journal of environmental management May 14, 2026

Scientific literature highlights that rising mean temperatures, combined with increasing frequency and duration of extreme heat events, pose risks to food security, particularly in climate sensitive regions of South Asia. These impacts are especially... read more

Transcriptomic sequencing analysis of the tumor microenvironment atlas and potential mechanisms of metastasis in papillary thyroid carcinoma.

Molecular immunology May 14, 2026

Papillary thyroid carcinoma (PTC) is the most prevalent thyroid malignancy and its incidence continues to rise. Although prognosis is generally favorable, overdiagnosis, overtreatment, and occasional lethal complications persist. To clarify the micro... read more

Measuring AI preparedness in health professions education: Evidence from a national survey of medical radiation science students and new graduates.

Radiography (London, England : 1995) May 14, 2026

INTRODUCTION: Artificial intelligence (AI) in medical radiation science (MRS) is increasingly embedded in everyday clinical workflows. As AI systems assume more operational roles, questions arise not only about technical competence, but about profess... read more

Potential and challenges of generative adversarial networks for super-resolution in 4D flow MRI.

Computers in biology and medicine May 14, 2026

Time-resolved three-dimensional phase-contrast MRI (4D Flow MRI) enables non-invasive quantification of blood flow and derivation of hemodynamic parameters. However, its clinical application is limited by low spatial resolution and noise, particularl... read more

Acoustic-based intraoperative assessment of femoral stem initial stability in cementless THA via sensitive frequency band identification.

Biomedical physics & engineering express May 14, 2026

Intraoperative assessment of femoral stem initial stability in cementless total hip arthroplasty (THA) predominantly relies on subjective tactile and auditory feedback, which lacks standardization and increases complication risks. This study develops... read more

CT-less TOF PET: challenges and innovations for quantitative imaging.

Physics in medicine and biology May 14, 2026

A decade has passed since the groundbreaking work by Defrise et al. (2012), which demonstrated that TOF PET imaging is self-correcting for a variety of physical degradation factors, most notably attenuation correction, which is currently based on CT ... read more

Cardiovascular Disease Events and Life Expectancy Lost Attributable to Machine Learning-Derived Dietary Networks: Evidence from Canadian National Nutrition Survey Linked to Routinely Collected Administrative Databases.

The Journal of nutrition May 14, 2026

BACKGROUND: Artificial intelligence and machine learning (ML) are transforming nutritional epidemiology by revealing dietary network structures invisible to conventional correlation-based methods. While traditional approaches fail to capture conditio... read more

Development and validation of multivariable prognostic machine learning models to identify patients at risk for inadequate bowel preparation when undergoing colonoscopy: a prospective, multicentre study.

BMJ open gastroenterology May 14, 2026

OBJECTIVE: Inadequate bowel preparation impairs the accuracy of colonoscopy and increases the burden on patients and healthcare systems. Consequently, the quality of bowel preparation is an important quality indicator. We aim to develop and validate ... read more

Machine learning models for outcome prediction of patients with ischaemic stroke undergoing reperfusion therapy: a systematic review and meta-analysis.

Stroke and vascular neurology May 14, 2026

BACKGROUND: Reperfusion therapy, including thrombolysis and thrombectomy, is crucial for ischaemic stroke treatment. However, patient outcomes often remain suboptimal. Conventional regression models show limited accuracy in predicting outcomes after ... read more

Achieving Ultra-High Acceleration Rates in 7T MRI Using Combined Controlled Aliasing in Parallel Imaging and Compressed Sensing with Deep-Learning-Based Image Reconstruction.

AJNR. American journal of neuroradiology May 14, 2026

BACKGROUND AND PURPOSE: Clinical adoption of 7T MRI has been limited by lengthy acquisitions. Acceleration techniques, such as controlled aliasing in parallel imaging (CAIPI) and compressed sensing (CS), can reduce scan time but are prone to artifact... read more

Artificial Intelligence Medical Compendium