We expect children to learn new words, skills, and ideas from various technologies. When learning from humans, children prefer people who are reliable and trustworthy, yet children also forgive people's occasional mistakes. Are the dynamics of childr...
BACKGROUND: To predict clinical important outcomes for colorectal liver metastases (CRLM) patients receiving colorectal resection with simultaneous liver resection by integrating demographic, clinical, laboratory, and genetic data.
BACKGROUND: Novel and scalable psychotherapies are urgently needed to address the depression and anxiety epidemic. Leveraging artificial intelligence (AI), a voice-based virtual coach named Lumen was developed to deliver problem solving treatment (PS...
Neurophysiologie clinique = Clinical neurophysiology
May 18, 2024
OBJECTIVE: The objective of this study was to develop artificial intelligence-based deep learning models and assess their potential utility and accuracy in diagnosing and predicting the future occurrence of diabetic distal sensorimotor polyneuropathy...
PURPOSE: To assess the efficacy of machine learning and radiomics analysis by computed tomography (CT) in presurgical setting, to predict RAS mutational status in colorectal liver metastases.
Journal of the American Heart Association
May 18, 2024
BACKGROUND: Patients with chronic limb-threatening ischemia (CLTI) face a high long-term mortality risk. Identifying novel mortality predictors and risk profiles would enable individual health care plan design and improved survival. We aimed to lever...
Stress recognition, particularly using machine learning (ML) with physiological data such as heart rate variability (HRV), holds promise for mental health interventions. However, limited datasets in affective computing and healthcare research can lea...
Platinum-based chemotherapy is the cornerstone treatment for female high-grade serous ovarian carcinoma (HGSOC), but choosing an appropriate treatment for patients hinges on their responsiveness to it. Currently, no available biomarkers can promptly ...
This study performed three-dimensional (3D) magnetic resonance imaging (MRI)-based statistical shape analysis (SSA) by comparing patellofemoral instability (PFI) and normal femur models, and developed a machine learning (ML)-based prediction model. T...
Journal of neuroengineering and rehabilitation
May 18, 2024
BACKGROUND: Proprioceptive impairments are common after stroke and are associated with worse motor recovery and poor rehabilitation outcomes. Motor learning may also be an important factor in motor recovery, and some evidence in healthy adults sugges...
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