We investigated whether machine learning methods could potentially identify a subgroup of persons with autism spectrum disorder (ASD) who show vitamin B6 responsiveness by selected phenotype variables. We analyzed the existing data from our intervent...
BACKGROUND: Deep learning has become a new trend of image recognition tasks in the field of medicine. We developed an automated gastritis detection system using double-contrast upper gastrointestinal barium X-ray radiography.
Clinical physiology and functional imaging
Oct 3, 2018
BACKGROUND: 18F-FDG-PET/CT has become a standard for assessing treatment response in patients with lymphoma. A subjective interpretation of the scan based on the Deauville 5-point scale has been widely adopted. However, inter-observer variability due...
International journal of computer assisted radiology and surgery
Oct 3, 2018
PURPOSE: Tuberculosis is a major global health threat claiming millions of lives each year. While the total number of tuberculosis cases has been decreasing over the last years, the rise of drug-resistant tuberculosis has reduced the chance of contro...
BACKGROUND: The conventional scores of the neuropsychological batteries are not fully optimized for diagnosing dementia despite their variety and abundance of information. To achieve low-cost high-accuracy diagnose performance for dementia using a ne...
The majority of insect species have a clearly defined larval stage during development. Larval nutrition is crucial for individuals' growth and development, and larval foraging success often depends on both resource availability and competition for th...
BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases. Machine learning techniques were introduced to evaluate the optimal predictive clinical model of NAFLD.
BACKGROUND: Sensitive skin refers to skin that tends to be highly responsive to stimuli such as physical, chemical, and psychological. Psychological factors play an important role in the pathology of sensitive skin.
OBJECTIVE: We aimed to identify optimal machine-learning methods for preoperative differentiation of sacral chordoma (SC) and sacral giant cell tumour (SGCT) based on 3D non-enhanced computed tomography (CT) and CT-enhanced (CTE) features.
: Identification of early-stage pulmonary adenocarcinomas before surgery, especially in cases of subcentimeter cancers, would be clinically important and could provide guidance to clinical decision making. In this study, we developed a deep learning ...
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