Computational intelligence and neuroscience
Jun 10, 2022
As a new type of electronic currency, bitcoin is more and more recognized and sought after by people, but its price fluctuation is more intense, the market has certain risks, and the price is difficult to be accurately predicted. The main purpose of ...
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Jun 9, 2022
Attenuation correction (AC) is essential for quantitative analysis and clinical diagnosis of single-photon emission computed tomography (SPECT) and positron emission tomography (PET). In clinical practice, computed tomography (CT) is utilized to gene...
The Journal of thoracic and cardiovascular surgery
Jun 9, 2022
OBJECTIVE: Acute kidney injury (AKI) after pediatric cardiac surgery with cardiopulmonary bypass (CPB) is a frequently reported complication. In this study we aimed to determine the oxygen delivery indexed to body surface area (Doi) threshold associa...
RATIONALE AND OBJECTIVES: Computed tomography (CT) is preferred for evaluating solitary pulmonary nodules (SPNs) but access or availability may be lacking, in addition, overlapping anatomy can hinder detection of SPNs on chest radiographs. We develop...
Medical care research and review : MCRR
Jun 9, 2022
There is growing interest in ensuring equity and guarding against bias in the use of risk scores produced by machine learning and artificial intelligence models. Risk scores are used to select patients who will receive outreach and support. Inappropr...
INTRODUCTION: Incisional hernias can complicate up to 25% of laparotomies, and successful repair remains a significant clinical challenge for surgeons. Recently, the surgical technique of ventral hernia repair (eTEP-RS) has been introduced. The metho...
Annual review of pharmacology and toxicology
Jun 9, 2022
The use of artificial intelligence (AI) and machine learning (ML) in pharmaceutical research and development has to date focused on research: target identification; docking-, fragment-, and motif-based generation of compound libraries; modeling of sy...
The application of machine learning (ML) to address population health challenges has received much less attention than its application in the clinical setting. One such challenge is addressing disparities in early childhood cognitive development-a co...
OBJECTIVE: To develop an ensemble deep learning model (DLM) predicting anterior cruciate ligament (ACL) tears from lateral knee radiographs and to evaluate its diagnostic performance.
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