[HTML][HTML] Considerations for diagnostic COVID-19 tests
O Vandenberg, D Martiny, O Rochas… - Nature Reviews …, 2021 - nature.com
During the early phase of the coronavirus disease 2019 (COVID-19) pandemic, design,
development, validation, verification and implementation of diagnostic tests were actively …
development, validation, verification and implementation of diagnostic tests were actively …
Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review
Objectives In this systematic review we aimed at assessing how artificial intelligence (AI),
including machine learning (ML) techniques have been deployed to predict, diagnose, and …
including machine learning (ML) techniques have been deployed to predict, diagnose, and …
Mortality prediction with adaptive feature importance recalibration for peritoneal dialysis patients
The study aims to develop AICare, an interpretable mortality prediction model, using
electronic medical records (EMR) from follow-up visits for end-stage renal disease (ESRD) …
electronic medical records (EMR) from follow-up visits for end-stage renal disease (ESRD) …
Precision medicine and machine learning towards the prediction of the outcome of potential celiac disease
Abstract Potential Celiac Patients (PCD) bear the Celiac Disease (CD) genetic
predisposition, a significant production of antihuman transglutaminase antibodies, but no …
predisposition, a significant production of antihuman transglutaminase antibodies, but no …
[HTML][HTML] Application of artificial intelligence in renal disease
L Yao, H Zhang, M Zhang, X Chen, J Zhang, J Huang… - Clinical eHealth, 2021 - Elsevier
Artificial intelligence (AI) has been applied widely in almost every area of our daily lives, due
to the growth of computing power, advances in methods and techniques, and the explosion …
to the growth of computing power, advances in methods and techniques, and the explosion …
Machine learning algorithms for the prediction of adverse prognosis in patients undergoing peritoneal dialysis
J Yang, J Wan, L Feng, S Hou, K Yv, L Xu… - BMC Medical Informatics …, 2024 - Springer
Background An appropriate prediction model for adverse prognosis before peritoneal
dialysis (PD) is lacking. Thus, we retrospectively analysed patients who underwent PD to …
dialysis (PD) is lacking. Thus, we retrospectively analysed patients who underwent PD to …
Comorbidity and in-hospital mortality in peritoneal dialysis patients: data of the Emilia Romagna region of Italy
Objective: Kidney failure increases in-hospital mortality (IHM); however, comorbidity is
crucial for predicting mortality in dialysis patients. Our aim was to evaluate the impact of …
crucial for predicting mortality in dialysis patients. Our aim was to evaluate the impact of …
The impact of artificial intelligence and big data on end-stage kidney disease treatments
C Diez-Sanmartin, A Sarasa-Cabezuelo… - Expert Systems with …, 2021 - Elsevier
In the field of medicine, decision-making has traditionally been carried out based on the best
available scientific information and the experience of specialists using data found in analog …
available scientific information and the experience of specialists using data found in analog …
Synchrony of biomarker variability indicates a critical transition: Application to mortality prediction in hemodialysis
Critical transition theory suggests that complex systems should experience increased
temporal variability just before abrupt state changes. We tested this hypothesis in 763 …
temporal variability just before abrupt state changes. We tested this hypothesis in 763 …
An explainable multimodal neural network architecture for predicting epilepsy comorbidities based on administrative claims data
Epilepsy is a complex brain disorder characterized by repetitive seizure events. Epilepsy
patients often suffer from various and severe physical and psychological comorbidities (eg …
patients often suffer from various and severe physical and psychological comorbidities (eg …