The need to separate the wheat from the chaff in medical informatics: Introducing a comprehensive checklist for the (self)-assessment of medical AI studies
F Cabitza, A Campagner - International Journal of Medical Informatics, 2021 - Elsevier
This editorial aims to contribute to the current debate about the quality of studies that apply
machine learning (ML) methodologies to medical data to extract value from them and …
machine learning (ML) methodologies to medical data to extract value from them and …
Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology
Artificial intelligence (AI) solutions that automatically extract information from digital histology
images have shown great promise for improving pathological diagnosis. Prior to routine use …
images have shown great promise for improving pathological diagnosis. Prior to routine use …
The predictive capabilities of Artificial Intelligence-based OCT analysis for age-related Macular Degeneration Progression—A systematic review
The era of artificial intelligence (AI) has revolutionized our daily lives and AI has become a
powerful force that is gradually transforming the field of medicine. Ophthalmology sits at the …
powerful force that is gradually transforming the field of medicine. Ophthalmology sits at the …
Counterfactual and factual reasoning over hypergraphs for interpretable clinical predictions on ehr
Abstract Electronic Health Record modeling is crucial for digital medicine. However, existing
models ignore higher-order interactions among medical codes and their causal relations …
models ignore higher-order interactions among medical codes and their causal relations …
Diffinfinite: Large mask-image synthesis via parallel random patch diffusion in histopathology
We present DiffInfinite, a hierarchical diffusion model that generates arbitrarily large
histological images while preserving long-range correlation structural information. Our …
histological images while preserving long-range correlation structural information. Our …
Improving uncertainty estimation with semi-supervised deep learning for COVID-19 detection using chest X-ray images
In this work we implement a COVID-19 infection detection system based on chest X-ray
images with uncertainty estimation. Uncertainty estimation is vital for safe usage of computer …
images with uncertainty estimation. Uncertainty estimation is vital for safe usage of computer …
Correcting data imbalance for semi-supervised covid-19 detection using x-ray chest images
A key factor in the fight against viral diseases such as the coronavirus (COVID-19) is the
identification of virus carriers as early and quickly as possible, in a cheap and efficient …
identification of virus carriers as early and quickly as possible, in a cheap and efficient …
Precision dentistry—what it is, where it fails (yet), and how to get there
F Schwendicke, J Krois - Clinical Oral Investigations, 2022 - Springer
Objectives Dentistry is stuck between the one-size-fits-all approach towards diagnostics and
therapy employed for a century and the era of stratified medicine. The present review …
therapy employed for a century and the era of stratified medicine. The present review …
Machine learning for health: algorithm auditing & quality control
L Oala, AG Murchison, P Balachandran… - Journal of medical …, 2021 - Springer
Developers proposing new machine learning for health (ML4H) tools often pledge to match
or even surpass the performance of existing tools, yet the reality is usually more …
or even surpass the performance of existing tools, yet the reality is usually more …
Stable clinical risk prediction against distribution shift in electronic health records
The availability of large-scale electronic health record datasets has led to the development
of artificial intelligence (AI) methods for clinical risk prediction that help improve patient care …
of artificial intelligence (AI) methods for clinical risk prediction that help improve patient care …