[HTML][HTML] Recent advancement in cancer detection using machine learning: Systematic survey of decades, comparisons and challenges
T Saba - Journal of infection and public health, 2020 - Elsevier
Cancer is a fatal illness often caused by genetic disorder aggregation and a variety of
pathological changes. Cancerous cells are abnormal areas often growing in any part of …
pathological changes. Cancerous cells are abnormal areas often growing in any part of …
Predicting the onset of diabetes with machine learning methods
CY Chou, DY Hsu, CH Chou - Journal of Personalized Medicine, 2023 - mdpi.com
The number of people suffering from diabetes in Taiwan has continued to rise in recent
years. According to the statistics of the International Diabetes Federation, about 537 million …
years. According to the statistics of the International Diabetes Federation, about 537 million …
Pima Indians diabetes mellitus classification based on machine learning (ML) algorithms
This paper proposes an e-diagnosis system based on machine learning (ML) algorithms to
be implemented on the Internet of Medical Things (IoMT) environment, particularly for …
be implemented on the Internet of Medical Things (IoMT) environment, particularly for …
Brain tumor segmentation using K‐means clustering and deep learning with synthetic data augmentation for classification
Image processing plays a major role in neurologists' clinical diagnosis in the medical field.
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Brain tumor detection and multi‐classification using advanced deep learning techniques
A brain tumor is an uncontrolled development of brain cells in brain cancer if not detected at
an early stage. Early brain tumor diagnosis plays a crucial role in treatment planning and …
an early stage. Early brain tumor diagnosis plays a crucial role in treatment planning and …
Brain tumor classification using meta-heuristic optimized convolutional neural networks
The field of medical image processing plays a significant role in brain tumor classification.
The survival rate of patients can be increased by diagnosing the tumor at an early stage …
The survival rate of patients can be increased by diagnosing the tumor at an early stage …
Prediction model using SMOTE, genetic algorithm and decision tree (PMSGD) for classification of diabetes mellitus
Diabetes mellitus is a well-known chronic disease that diminishes the insulin producing
capability of the human body. This results in high blood sugar level which might lead to …
capability of the human body. This results in high blood sugar level which might lead to …
Comparative performance analysis of quantum machine learning with deep learning for diabetes prediction
Background Diabetes, the fastest growing health emergency, has created several life-
threatening challenges to public health globally. It is a metabolic disorder and triggers many …
threatening challenges to public health globally. It is a metabolic disorder and triggers many …
Reported adverse effects and attitudes among Arab populations following COVID-19 vaccination: a large-scale multinational study implementing machine learning …
Background: The unprecedented global spread of coronavirus disease 2019 (COVID-19)
has imposed huge challenges on the healthcare facilities, and impacted every aspect of life …
has imposed huge challenges on the healthcare facilities, and impacted every aspect of life …
Using recurrent neural networks for predicting type-2 diabetes from genomic and tabular data
The development of genomic technology for smart diagnosis and therapies for various
diseases has lately been the most demanding area for computer-aided diagnostic and …
diseases has lately been the most demanding area for computer-aided diagnostic and …