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)
Aug 28, 2024
PURPOSE: The purpose of this study is to develop an automated method using deep learning for the reliable and precise quantification of left ventricle structure and function from echocardiogram videos, eliminating the need to identify end-systolic an...
Multi-task learning (MTL) methods are widely applied in breast imaging for lesion area perception and classification to assist in breast cancer diagnosis and personalized treatment. A typical paradigm of MTL is the shared-backbone network architectur...
Gait analysis systems are critical for assessing motor function in rehabilitation and elderly care. This study aimed to develop and optimize an abnormal gait classification algorithm considering joint impairments using inertial measurement units (IMU...
Gait speed is increasingly recognized as an important health indicator. However, gait analysis in clinical settings often encounters inconsistencies due to methodological variability and resource constraints. To address these challenges, GaitKeeper u...
Simulation in healthcare, empowered by big data analytics and artificial intelligence (AI), has the potential to drive transformative innovations towards enhanced interprofessional collaboration (IPC). This convergence of technologies revolutionizes ...
BACKGROUND: Acute biliary pancreatitis (ABP) is a clinical common acute abdomen. After the first pancreatitis, relapse rate is high, which seriously affects human life and health and causes great economic burdens to family and society. According to a...
BACKGROUND: Pulmonary tuberculosis (PTB) is a prevalent chronic disease associated with a significant economic burden on patients. Using machine learning to predict hospitalization costs can allocate medical resources effectively and optimize the cos...
Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) are vision related complications prominently found in diabetic patients. The early identification of DR/DME grades facilitates the devising of an appropriate treatment plan, which ultimately ...
Titrating tacrolimus concentration in liver transplantation recipients remains a challenge in the early post-transplant period. This multicenter retrospective cohort study aimed to develop and validate a machine-learning algorithm to predict tacrolim...
Deep learning techniques were used in ophthalmology to develop artificial intelligence (AI) models for predicting the short-term effectiveness of anti-VEGF therapy in patients with macular edema secondary to branch retinal vein occlusion (BRVO-ME). 1...
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