The aim of this study was to develop a computer expert system that could reproduce a pathologist's diagnosis of iron deficiency from the data obtained from blood tests. 275 cases were collected for construction and testing of the expert system. The expert system used a combination of fuzzy set logic and cut-off points from 14 parameters to arrive at one of 5 diagnostic categories graded from "iron deficient" to "no evidence of iron deficiency". The agreement between pathologist and expert system was 0.91 (Spearman rank correlation coefficient) in the learning population; this dropped to 0.79 in the test population. Absolute agreement on diagnostic category was reached in 71% of cases. In no case was there disagreement by more than 3 grades.
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http://dx.doi.org/10.1080/00313029400169071 | DOI Listing |
JMIR Res Protoc
January 2025
Institute for Health Care Management and Research, University of Duisburg-Essen, Essen, Germany.
Background: Artificial intelligence (AI)-based clinical decision support systems (CDSS) have been developed for several diseases. However, despite the potential to improve the quality of care and thereby positively impact patient-relevant outcomes, the majority of AI-based CDSS have not been adopted in standard care. Possible reasons for this include barriers in the implementation and a nonuser-oriented development approach, resulting in reduced user acceptance.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Pharmacy, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China.
Objective: This study aims to construct a training course and quality evaluation index system for chronic disease Medication Therapy Management service (MTMs) that is suitable for China's national conditions. It seeks to provide tools and a scientific foundation for assessing the quality of MTMs training.
Methods: Drawing from domestic and international literature and combining with the practice of chronic disease medication management by Chinese pharmacists, a preliminary framework for the evaluation index system was established.
J Med Chem
January 2025
Medicinal Chemistry and Bioinformatics Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Retrosynthesis is a strategy to analyze the synthetic routes for target molecules in medicinal chemistry. However, traditional retrosynthesis predictions performed by chemists and rule-based expert systems struggle to adapt to the vast chemical space of real-world scenarios. Artificial intelligence (AI) has revolutionized retrosynthesis prediction in recent decades, significantly increasing the accuracy and diversity of predictions for target compounds.
View Article and Find Full Text PDFLung Cancer Manag
July 2024
Department of Pulmonology, I.M. Sechenov First Moscow State Medical University, Moscow 678554, Russian Federation.
Lung cancer is still diagnosed at an advanced stage due to lack of early disease symptoms. We have techniques and equipment for rapid on site evaluation of pulmonary lesions. However, with new technology or a combination of technologies in the diagnostic suite the cost of biopsy is rising.
View Article and Find Full Text PDFCan Assoc Radiol J
January 2025
North York General Hospital, Toronto, ON, Canada.
The Canadian Association of Radiologists (CAR) Central Nervous System Expert Panel is made up of physicians from the disciplines of radiology, emergency medicine, neurosurgery, and neurology, a patient advisor, and an epidemiologist/guideline methodologist. After developing a list of 24 clinical/diagnostic scenarios, a rapid scoping review was undertaken to identify systematically produced referral guidelines that provide recommendations for one or more of these clinical/diagnostic scenarios. Recommendations from 55 guidelines and contextualization criteria in the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) for guidelines framework were used to develop 51 recommendation statements across the 24 scenarios.
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