AIMC Topic: Diagnostic Techniques and Procedures

Clear Filters Showing 11 to 20 of 30 articles

Enhancing ontology-driven diagnostic reasoning with a symptom-dependency-aware Naïve Bayes classifier.

BMC bioinformatics
BACKGROUND: Ontology has attracted substantial attention from both academia and industry. Handling uncertainty reasoning is important in researching ontology. For example, when a patient is suffering from cirrhosis, the appearance of abdominal vein v...

[Data-driven integrated diagnostics: the natural evolution of clinical chemistry?].

Nederlands tijdschrift voor geneeskunde
In the near future, making a correct medical diagnosis will be increasingly supported by artificial intelligence. The development of algorithms that integrate all data from an individual into the diagnostic process calls for a multidisciplinary appro...

Evaluation of supervised machine-learning algorithms to distinguish between inflammatory bowel disease and alimentary lymphoma in cats.

Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc
Inflammatory bowel disease (IBD) and alimentary lymphoma (ALA) are common gastrointestinal diseases in cats. The very similar clinical signs and histopathologic features of these diseases make the distinction between them diagnostically challenging. ...

Dense Annotation of Free-Text Critical Care Discharge Summaries from an Indian Hospital and Associated Performance of a Clinical NLP Annotator.

Journal of medical systems
Electronic Health Record (EHR) use in India is generally poor, and structured clinical information is mostly lacking. This work is the first attempt aimed at evaluating unstructured text mining for extracting relevant clinical information from Indian...

An electronic medical record system with treatment recommendations based on patient similarity.

Journal of medical systems
As the core of health information technology (HIT), electronic medical record (EMR) systems have been changing to meet health care demands. To construct a new-generation EMR system framework with the capability of self-learning and real-time feedback...

Empirical assessment of bias in machine learning diagnostic test accuracy studies.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Machine learning (ML) diagnostic tools have significant potential to improve health care. However, methodological pitfalls may affect diagnostic test accuracy studies used to appraise such tools. We aimed to evaluate the prevalence and rep...

Should we have a right to refuse diagnostics and treatment planning by artificial intelligence?

Medicine, health care, and philosophy
Should we be allowed to refuse any involvement of artificial intelligence (AI) technology in diagnosis and treatment planning? This is the relevant question posed by Ploug and Holm in a recent article in Medicine, Health Care and Philosophy. In this ...

The right to refuse diagnostics and treatment planning by artificial intelligence.

Medicine, health care, and philosophy
In an analysis of artificially intelligent systems for medical diagnostics and treatment planning we argue that patients should be able to exercise a right to withdraw from AI diagnostics and treatment planning for reasons related to (1) the physicia...

Robotic Systems Involved in the Diagnosis of Neurodegenerative Diseases.

Advances in experimental medicine and biology
The continuing development of robotics on the one hand and, on the other hand, the estimated relative growth in the number of elderly individuals suffering from neurodegenerative diseases raises the question of which contribution these powerful syste...