AIMC Topic: Humans

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Comparative Analysis of Nomogram and Machine Learning Models for Predicting Axillary Lymph Node Metastasis in Early-Stage Breast Cancer: A Study on Clinically and Ultrasound-Negative Axillary Cases Across Two Centers.

Ultrasound in medicine & biology
OBJECTIVE: Early and accurate prediction of axillary lymph node metastasis (ALNM) is crucial in determining appropriate treatment strategies for patients with early-stage breast cancer. The aim of this study was to evaluate the efficacy of radiomic f...

Assessing population-based to personalized planning strategies for head and neck adaptive radiotherapy.

Journal of applied clinical medical physics
PURPOSE: Optimal head-and-neck cancer (HNC) treatment planning requires accurate and feasible planning goals to meet dosimetric constraints and generate robust online adaptive treatment plans. A new x-ray-based adaptive radiotherapy (ART) treatment p...

Machine learning in predicting cauda equina imaging outcomes- a solution to the problem.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: Cauda Equina Syndrome (CES) is a rare surgical emergency. The implications for loss of quality of life through delayed management are high, though no clinical symptom is pathognomonic in its diagnosis. We describe how machine learning based ...

Real-time 3D MR guided radiation therapy through orthogonal MR imaging and manifold learning.

Medical physics
BACKGROUND: In magnetic resonance image (MRI)-guided radiotherapy (MRgRT), 2D rapid imaging is commonly used to track moving targets with high temporal frequency to minimize gating latency. However, anatomical motion is not constrained to 2D, and a p...

Breast radiotherapy planning: A decision-making framework using deep learning.

Medical physics
BACKGROUND: Effective breast cancer treatment planning requires balancing tumor control while minimizing radiation exposure to healthy tissues. Choosing between intensity-modulated radiation therapy (IMRT) and three-dimensional conformal radiation th...

Deep learning based super-resolution for CBCT dose reduction in radiotherapy.

Medical physics
BACKGROUND: Cone-beam computed tomography (CBCT) is a crucial daily imaging modality in image-guided and adaptive radiotherapy. However, the use of ionizing radiation in CBCT imaging increases the risk of secondary cancers, which is particularly conc...

Digitalization of health care in low- and middle-income countries.

Bulletin of the World Health Organization
The rising incidence of noncommunicable diseases, combined with the costs of mitigating climate change, sovereign debt and regional conflicts, is undermining global health security and threatening progress towards achieving the sustainable developmen...

Exploring the potential and limitations of artificial intelligence in animal anatomy.

Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft
BACKGROUND: Artificial intelligence (AI) is revolutionizing veterinary medicine, particularly in the domain of veterinary anatomy. At present, there is no existing review article in the literature that examines the prospects and challenges associated...

Leveraging deep transfer learning and explainable AI for accurate COVID-19 diagnosis: Insights from a multi-national chest CT scan study.

Computers in biology and medicine
The COVID-19 pandemic has emerged as a global health crisis, impacting millions worldwide. Although chest computed tomography (CT) scan images are pivotal in diagnosing COVID-19, their manual interpretation by radiologists is time-consuming and poten...

A smart CardioSenseNet framework with advanced data processing models for precise heart disease detection.

Computers in biology and medicine
Heart diseases remain one of the leading causes of death worldwide. As a result, early and accurate diagnostics have become an urgent need for treatment and management. Most of the conventional methods adopted tend to have major drawbacks: the issues...