AIMC Topic: Female

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Prediction of complication related death after radical cystectomy for bladder cancer with machine learning methodology.

Scandinavian journal of urology
To create a pre-operatively usable tool to identify patients at high risk of early death (within 90 days post-operatively) after radical cystectomy and to assess potential risk factors for post-operative and surgery related mortality. Material consi...

Multi-criterion mammographic risk analysis supported with multi-label fuzzy-rough feature selection.

Artificial intelligence in medicine
CONTEXT AND BACKGROUND: Breast cancer is one of the most common diseases threatening the human lives globally, requiring effective and early risk analysis for which learning classifiers supported with automated feature selection offer a potential rob...

Gait can reveal sleep quality with machine learning models.

PloS one
Sleep quality is an important health indicator, and the current measurements of sleep rely on questionnaires, polysomnography, etc., which are intrusive, expensive or time consuming. Therefore, a more nonintrusive, inexpensive and convenient method n...

Diagnosis and classification of pediatric acute appendicitis by artificial intelligence methods: An investigator-independent approach.

PloS one
Acute appendicitis is one of the major causes for emergency surgery in childhood and adolescence. Appendectomy is still the therapy of choice, but conservative strategies are increasingly being studied for uncomplicated inflammation. Diagnosis of acu...

Multi-Objective Optimization for Personalized Prediction of Venous Thromboembolism in Ovarian Cancer Patients.

IEEE journal of biomedical and health informatics
Thrombotic events are one of the leading causes of mortality and morbidity related to cancer, with ovarian cancer having one of the highest incidence rates. The need to prevent these events through the prescription of adequate schemes of antithrombot...

Evaluating the performance of a predictive modeling approach to identifying members at high-risk of hospitalization.

Journal of medical economics
To evaluate the risk-of-hospitalization (ROH) models developed at Blue Cross Blue Shield of Louisiana (BCBSLA) and compare this approach to the DxCG risk-score algorithms utilized by many health plans. Time zero for this study was December 31, 2016....

Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.

Ophthalmology
PURPOSE: To develop and validate a deep learning (DL) algorithm that predicts referable glaucomatous optic neuropathy (GON) and optic nerve head (ONH) features from color fundus images, to determine the relative importance of these features in referr...

Patient clustering improves efficiency of federated machine learning to predict mortality and hospital stay time using distributed electronic medical records.

Journal of biomedical informatics
Electronic medical records (EMRs) support the development of machine learning algorithms for predicting disease incidence, patient response to treatment, and other healthcare events. But so far most algorithms have been centralized, taking little acc...

Using machine learning to understand neuromorphological change and image-based biomarker identification in Cavalier King Charles Spaniels with Chiari-like malformation-associated pain and syringomyelia.

Journal of veterinary internal medicine
BACKGROUND: Chiari-like malformation (CM) is a complex malformation of the skull and cranial cervical vertebrae that potentially results in pain and secondary syringomyelia (SM). Chiari-like malformation-associated pain (CM-P) can be challenging to d...

Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives.

Radiology
Although computer-aided diagnosis (CAD) is widely used in mammography, conventional CAD programs that use prompts to indicate potential cancers on the mammograms have not led to an improvement in diagnostic accuracy. Because of the advances in machin...