This work is to investigate the diagnostic value of a deep learning-based magnetic resonance imaging (MRI) image segmentation (IS) technique for shoulder joint injuries (SJIs) in swimmers. A novel multi-scale feature fusion network (MSFFN) is develop...
Skin Cancer, which leads to a large number of deaths annually, has been extensively considered as the most lethal tumor around the world. Accurate detection of skin cancer in its early stage can significantly raise the survival rate of patients and r...
This study investigated the utilization of digital phenotypes and machine learning algorithms to predict impending panic symptoms in patients with mood and anxiety disorders. A cohort of 43 patients was monitored over a two-year period, with data col...
There is no doubt that social media sites have provided many benefits to humanity, such as sharing information continuously and communicating with others easily. It also seems that social media sites have many advantages, but in addition to these adv...
Medical image classification requires labeled, task-specific datasets which are used to train deep learning networks de novo, or to fine-tune foundation models. However, this process is computationally and technically demanding. In language processin...
BACKGROUND: Image-driven specialisms such as radiology and pathology are at the forefront of medical artificial intelligence (AI) innovation. Many believe that AI will lead to significant shifts in professional roles, so it is vital to investigate ho...
We address an open problem in the philosophy of artificial intelligence (AI): how to justify the epistemic attitudes we have towards the trustworthiness of AI systems. The problem is important, as providing reasons to believe that AI systems are wort...
OBJECTIVE: To develop and validate an artificial intelligence (AI)-driven tool for automated segmentation of the pulp cavity system of mandibular molars on cone-beam computed tomography (CBCT) images.
International journal of technology assessment in health care
Nov 21, 2024
OBJECTIVES: Artificial intelligence (AI)-based health technologies (AIHTs) have already been applied in clinical practice. However, there is currently no standardized framework for evaluating them based on the principles of health technology assessme...
UNLABELLED: Machine learning (ML) based on remote video has shown ideal diagnostic value in autism spectrum disorder (ASD). Here, we conducted a meta-analysis of the diagnostic value of home video-based ML in ASD. Relevant articles were systematicall...
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