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Urgency Prediction for Medical Laboratory Tests Through Optimal Sparse Decision Tree: Case Study With Echocardiograms.
JMIR AI
January 2025
Department of Information Systems and Business Analytics, Iowa State University, Ames, IA, United States.
Background: In the contemporary realm of health care, laboratory tests stand as cornerstone components, driving the advancement of precision medicine. These tests offer intricate insights into a variety of medical conditions, thereby facilitating diagnosis, prognosis, and treatments. However, the accessibility of certain tests is hindered by factors such as high costs, a shortage of specialized personnel, or geographic disparities, posing obstacles to achieving equitable health care.
View Article and Find Full Text PDFDiagnostic Decision-Making Variability Between Novice and Expert Optometrists for Glaucoma: Comparative Analysis to Inform AI System Design.
JMIR Med Inform
January 2025
Department of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada.
Background: While expert optometrists tend to rely on a deep understanding of the disease and intuitive pattern recognition, those with less experience may depend more on extensive data, comparisons, and external guidance. Understanding these variations is important for developing artificial intelligence (AI) systems that can effectively support optometrists with varying degrees of experience and minimize decision inconsistencies.
Objective: The main objective of this study is to identify and analyze the variations in diagnostic decision-making approaches between novice and expert optometrists.
Diagnostic accuracy of node-RADS for the detection of lymph node invasion: a systematic review and meta-analysis.
Eur Radiol
January 2025
Department of Urological Surgical, JiangNan University Medical Center, Wuxi, China.
Objective: To conduct a meta-analysis assessing the diagnostic performance of the node reporting and data system (Node-RADS) for detecting lymph node (LN) invasion.
Method: We performed a systematic literature search of online scientific publication databases from inception up to July 31, 2024. We used the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) to assess the study quality, and heterogeneity was determined by the Q-test and measured with I statistics.
Review of pretreatment and analytical methods for environmental endocrine disruptors: Phthalates.
Environ Toxicol Chem
January 2025
School of Energy and Environmental Engineering, University of Science and Technology Beijing, 100083China.
Phthalates, known as phthalate esters (PAEs), are among the most ubiquitous pervasive env7ironmental endocrine disruptors (EEDs), extensively utilized globally in various facets of modern life due to their irreplaceable role as plasticizers. The exponential production and utilization of plastic goods have substantially escalated plastic waste accumulation. Consequently, PAEs have infiltrated the environment, contaminating food and drinking water reservoirs, posing notable threats to human health.
View Article and Find Full Text PDFDeletion of atypical type II restriction genes in Clostridium cellulovorans using a Cas9-based gene editing system.
Appl Microbiol Biotechnol
January 2025
Chair of Microbiology, Technical University of Munich, TUM School of Life Science, Emil-Ramann-Str. 4, 85354, Freising, Germany.
The anaerobic bacterium Clostridium cellulovorans is a promising candidate for the sustainable production of biofuels and platform chemicals due to its cellulolytic properties. However, the genomic engineering of the species is hampered because of its poor genetic accessibility and the lack of genetic tools. To overcome this limitation, a protocol for triparental conjugation was established that enables the reliable transfer of vectors for markerless chromosomal modification into C.
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