[HTML][HTML] Artificial intelligence applications in health care practice: scoping review
Background Artificial intelligence (AI) is often heralded as a potential disruptor that will
transform the practice of medicine. The amount of data collected and available in health …
transform the practice of medicine. The amount of data collected and available in health …
Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease
The medical field has seen a rapid increase in the development of artificial intelligence (AI)-
based prediction models. With the introduction of such AI-based prediction model tools and …
based prediction models. With the introduction of such AI-based prediction model tools and …
[HTML][HTML] Human-centered design to address biases in artificial intelligence
The potential of artificial intelligence (AI) to reduce health care disparities and inequities is
recognized, but it can also exacerbate these issues if not implemented in an equitable …
recognized, but it can also exacerbate these issues if not implemented in an equitable …
[HTML][HTML] SKCV: Stratified K-fold cross-validation on ML classifiers for predicting cervical cancer
Cancer is the unregulated development of abnormal cells in the human body system.
Cervical cancer, also known as cervix cancer, develops on the cervix's surface. This causes …
Cervical cancer, also known as cervix cancer, develops on the cervix's surface. This causes …
[HTML][HTML] Methodological guidance for the evaluation and updating of clinical prediction models: a systematic review
MAE Binuya, EG Engelhardt, W Schats… - BMC Medical Research …, 2022 - Springer
Background Clinical prediction models are often not evaluated properly in specific settings
or updated, for instance, with information from new markers. These key steps are needed …
or updated, for instance, with information from new markers. These key steps are needed …
TRIPOD+ AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual
Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting …
Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting …
Artificial intelligence and machine learning approaches using gene expression and variant data for personalized medicine
S Vadapalli, H Abdelhalim, S Zeeshan… - Briefings in …, 2022 - academic.oup.com
Precision medicine uses genetic, environmental and lifestyle factors to more accurately
diagnose and treat disease in specific groups of patients, and it is considered one of the …
diagnose and treat disease in specific groups of patients, and it is considered one of the …
[HTML][HTML] Artificial intelligence in hematological diagnostics: Game changer or gadget?
W Walter, C Pohlkamp, M Meggendorfer, N Nadarajah… - Blood Reviews, 2023 - Elsevier
The future of clinical diagnosis and treatment of hematologic diseases will inevitably involve
the integration of artificial intelligence (AI)-based systems into routine practice to support the …
the integration of artificial intelligence (AI)-based systems into routine practice to support the …
Harnessing big data analytics for healthcare: A comprehensive review of frameworks, implications, applications, and impacts
Big Data Analytics (BDA) has garnered significant attention in both academia and industries,
particularly in sectors such as healthcare, owing to the exponential growth of data and …
particularly in sectors such as healthcare, owing to the exponential growth of data and …
[HTML][HTML] Perspectives on validation of clinical predictive algorithms
The generalizability of predictive algorithms is of key relevance to application in clinical
practice. We provide an overview of three types of generalizability, based on existing …
practice. We provide an overview of three types of generalizability, based on existing …