A survey on medical explainable AI (XAI): recent progress, explainability approach, human interaction and scoring system
RK Sheu, MS Pardeshi - Sensors, 2022 - mdpi.com
The emerging field of eXplainable AI (XAI) in the medical domain is considered to be of
utmost importance. Meanwhile, incorporating explanations in the medical domain with …
utmost importance. Meanwhile, incorporating explanations in the medical domain with …
[HTML][HTML] Process mining and data mining applications in the domain of chronic diseases: A systematic review
The widespread use of information technology in healthcare leads to extensive data
collection, which can be utilised to enhance patient care and manage chronic illnesses. Our …
collection, which can be utilised to enhance patient care and manage chronic illnesses. Our …
Ensemble learning-based feature engineering to analyze maternal health during pregnancy and health risk prediction
Maternal health is an important aspect of women's health during pregnancy, childbirth, and
the postpartum period. Specifically, during pregnancy, different health factors like age, blood …
the postpartum period. Specifically, during pregnancy, different health factors like age, blood …
Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients
Mortality prediction for intensive care unit (ICU) patients is crucial for improving outcomes
and efficient utilization of resources. Accessibility of electronic health records (EHR) has …
and efficient utilization of resources. Accessibility of electronic health records (EHR) has …
Prediction of unplanned 30-day readmission for ICU patients with heart failure
Abstract Background Intensive Care Unit (ICU) readmissions in patients with heart failure
(HF) result in a significant risk of death and financial burden for patients and healthcare …
(HF) result in a significant risk of death and financial burden for patients and healthcare …
Effect of a process mining based pre-processing step in prediction of the critical health outcomes
Predicting critical health outcomes such as patient mortality and hospital readmission is
essential for improving survivability. However, healthcare datasets have many concurrences …
essential for improving survivability. However, healthcare datasets have many concurrences …
Study on diabetic conditions monitoring using deep learning application
RK Kanna, R Chandrasekaran… - 2023 3rd …, 2023 - ieeexplore.ieee.org
The application of technology search in full industrial management has been shown to be
advanced to some extent by deep learning models. The replacement of activities that need …
advanced to some extent by deep learning models. The replacement of activities that need …
A deep learning approach for inpatient length of stay and mortality prediction
Purpose Accurate prediction of the Length of Stay (LoS) and mortality in the Intensive Care
Unit (ICU) is crucial for effective hospital management, and it can assist clinicians for real …
Unit (ICU) is crucial for effective hospital management, and it can assist clinicians for real …
An effective correlation-based data modeling framework for automatic diabetes prediction using machine and deep learning techniques
The rising risk of diabetes, particularly in emerging countries, highlights the importance of
early detection. Manual prediction can be a challenging task, leading to the need for …
early detection. Manual prediction can be a challenging task, leading to the need for …
[HTML][HTML] Knowledge-based dynamic prompt learning for multi-label disease diagnosis
Pretrained language models (PLMs) have been developed rapidly which establish
impressive performance on many open-domain downstream tasks. However, conducting …
impressive performance on many open-domain downstream tasks. However, conducting …