Machine-learning-based disease diagnosis: A comprehensive review

MM Ahsan, SA Luna, Z Siddique - Healthcare, 2022 - mdpi.com
Globally, there is a substantial unmet need to diagnose various diseases effectively. The
complexity of the different disease mechanisms and underlying symptoms of the patient …

Machine-learning approaches in COVID-19 survival analysis and discharge-time likelihood prediction using clinical data

M Nemati, J Ansary, N Nemati - Patterns, 2020 - cell.com
As a highly contagious respiratory disease, COVID-19 has yielded high mortality rates since
its emergence in December 2019. As the number of COVID-19 cases soars in epicenters …

[HTML][HTML] A forecasting approach for hospital bed capacity planning using machine learning and deep learning with application to public hospitals

Y Mahmoudian, A Nemati, AS Safaei - Healthcare Analytics, 2023 - Elsevier
Abstract Hospital Bed Capacity (HBC) planning affects economic and social sustainability in
healthcare through bed capacity efficiency and medical treatment accessibility …

The Role of Machine Learning in Health Care Diagnosis

RK Shukla, M Rakhra, D Singh… - 2022 4th International …, 2022 - ieeexplore.ieee.org
During our daily lives, artificial intelligence is becoming more ubiquitous. The two artificial
intelligence (AI) descendants are machine learning and deep learning. The new frontier of …

Preparation and characterisation of polycaprolactone–fibroin nanofibrous scaffolds containing allicin

B Mollaghadimi - IET nanobiotechnology, 2022 - Wiley Online Library
Polycaprolactone (PCL) and silk fibroin are used to make nanofiber wound dressings, and
then allicin is added to PCL and silk fibroin to expand antibacterial properties. The polymer …

Influence of bias and variance in selection of machine learning classifiers for biomedical applications

P Chakraborty, SS Rafiammal, C Tharini… - Smart Data Intelligence …, 2022 - Springer
Abstract Machine learning classifiers play vital role in biomedical signals analysis and
disease diagnosis. The selection of proper machine learning model for disease detection is …

Machine learning vs. survival analysis models: a study on right censored heart failure data

B Srujana, D Verma, S Naqvi - Communications in Statistics …, 2024 - Taylor & Francis
Abstract Machine Learning Models are known to understand the intricacies of the data well,
but native ML models cannot be used in time-to-event analysis due to censoring. In this …

Multiclass classification of liver diseases using optimized machine learning classifiers

P Verma, K Deshmukh… - … and Knowledge Economy …, 2023 - ieeexplore.ieee.org
Chronic hepatitis C is associated with two severe, perhaps fatal health problems: cirrhosis
and liver cancer. Chronic liver disease is an exceedingly dangerous condition requiring …

An optimal modified faster region cnn model for diagnosis of liver diseases from ultrasound images

V Antony Asir Daniel, J Jeha - IETE Journal of Research, 2024 - Taylor & Francis
In recent years, the rate of mortality and morbidity increased due to uncontrolled conditions
of liver diseases. Liver disorders are mainly caused because of inhalation of toxic gases …

Prediction of drug targets related to HCC metastasis from the perspective of programmed cell death based on transformer

Y Huang, F Fang, L Liu, K Chen, Y Du - Future Generation Computer …, 2024 - Elsevier
Hepatocellular carcinoma (HCC) ranks as the sixth most prevalent cancer globally and the
third leading cause of cancer-related deaths. The early diagnosis of HCC is challenging …