Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.
BACKGROUND: Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as variant interpretation or reporting are inefficient. To overcome this situation, we developed REDBot as an automated software package for accurate and direct generation of clinical diagnostic reports for prenatal and products of conception (POC) samples.
BACKGROUND: A microscopic analysis of tissue is the gold standard for cancer detection. Hematoxylin-eosin (HE) for the reporting of prostate biopsy (PB) is conventionally based on fixation, processing, acquisition of glass slides, and analysis with an analog microscope by a local pathologist. Digitalization and real-time remote access to images could enhance the reporting process, and form the bas...
Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its implementation will be focused on the automatization tasks, i...
The risk stratification system of the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) for thyroid nodules is af...
The CONSORT 2010 statement provides minimum guidelines for reporting randomised trials. Its widespread use has been instrumental in ensuring transpare...
The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the mi...
The SPIRIT 2013 (The Standard Protocol Items: Recommendations for Interventional Trials) statement aims to improve the completeness of clinical trial ...
The CONSORT 2010 (Consolidated Standards of Reporting Trials) statement provides minimum guidelines for reporting randomised trials. Its widespread us...
The CONSORT 2010 statement provides minimum guidelines for reporting randomized trials. Its widespread use has been instrumental in ensuring transpare...
The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the mi...
Due to datasets have continuously grown, efforts have been performed in the attempt to solve the problem related to the large amount of unlabeled data...
BACKGROUND: Critical thyroid nodule features are contained in unstructured ultrasound (US) reports. The Thyroid Imaging, Reporting, and Data System (T...
Diagnosis prediction is an important predictive task in health care that aims to predict the patient future diagnosis based on their historical medica...
Colorectal cancer has a great incidence rate worldwide, but its early detection significantly increases the survival rate. Colonoscopy is the gold sta...
Deep auto-encoders (DAEs) have achieved great success in learning data representations via the powerful representability of neural networks. But most ...
Background The coronavirus disease 2019 (COVID-19) pandemic has spread across the globe with alarming speed, morbidity, and mortality. Immediate triag...
Detecting and analyzing patient insights from social media enables healthcare givers to better understand what patients want and also to identify thei...
Substantial progress has been made towards implementing automated radiology reporting models based on deep learning (DL). This is due to the introduct...
PURPOSE: Deep learning has recently shown its outstanding performance in biomedical image semantic segmentation. Most biomedical semantic segmentation...
The existing flaws in both conducting and reporting of research have been outlined and criticized in the past. Weak research design, poor methodology,...