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http://dx.doi.org/10.5935/0101-2800.20170024 | DOI Listing |
Introduction: The U.S. Army Telemedicine and Advanced Technology Research Center Advanced Medical Technology Initiative (AMTI) demonstrate key emerging technologies related to military medicine.
View Article and Find Full Text PDFEur Rev Med Pharmacol Sci
July 2023
Medical Faculty of Novi Sad, The University of Novi Sad, Novi Sad, Serbia.
Objective: The main aim of this study was to develop a machine-learning-based model for predicting the success of labor induction (IOL). To that end, the clinical and ultrasound parameters that affect the successfulness of labor induction were assessed. Then, a new ultrasound scoring system (USS) was developed and assessed.
View Article and Find Full Text PDFImplement Sci
May 2022
Department of General Practice, University of Melbourne, Melbourne, Australia.
Background: We developed a colorectal cancer risk prediction tool ('CRISP') to provide individualised risk-based advice for colorectal cancer screening. Using known environmental, behavioural, and familial risk factors, CRISP was designed to facilitate tailored screening advice to patients aged 50 to 74 years in general practice. In parallel to a randomised controlled trial of the CRISP tool, we developed and evaluated an evidence-based implementation strategy.
View Article and Find Full Text PDFDiagnostics (Basel)
July 2020
Deapartment of Pathology, Microbiology and Forensic Medicine, Jordan University, Amman 11924, Jordan.
() can cause gastritis, peptic ulcer diseases and gastric carcinoma. Endoscopy as the gold standard method of diagnosis is an invasive procedure that might not be suitable in all scenarios. Therefore, this first study in Jordan aimed to assess the non-invasive C urea breath test (UBT) and stool antigen test for diagnosis of infection and the successfulness of eradication therapy as alternatives for endoscopy.
View Article and Find Full Text PDFBiomolecules
December 2019
Battelle Center for Mathematical Medicine, Nationwide Children's Hospital, Columbus, OH 43205, USA.
Accurate prediction of protein stability changes resulting from amino acid substitutions is of utmost importance in medicine to better understand which mutations are deleterious, leading to diseases, and which are neutral. Since conducting wet lab experiments to get a better understanding of protein mutations is costly and time consuming, and because of huge number of possible mutations the need of computational methods that could accurately predict effects of amino acid mutations is of greatest importance. In this research, we present a robust methodology to predict the energy changes of a proteins upon mutations.
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