Reimagining multi-criterion decision making by data-driven methods based on machine learning: A literature review
Multi-criterion decision making (MCDM) methods can derive alternative rankings as
solutions to decision-making problems based on survey or historical data about the …
solutions to decision-making problems based on survey or historical data about the …
Computer-aided detection and classification of monkeypox and chickenpox lesion in human subjects using deep learning framework
Monkeypox is a zoonotic viral disease caused by the monkeypox virus. After its recent
outbreak, it has become clear that a rapid, accurate, and reliable diagnosis may help reduce …
outbreak, it has become clear that a rapid, accurate, and reliable diagnosis may help reduce …
Impact of feature scaling on machine learning models for the diagnosis of diabetes
Due to its high prevalence and incidence, diabetes is considered significant public health.
Since diabetes has no known cure, early diagnosis plays a vital role in effectively managing …
Since diabetes has no known cure, early diagnosis plays a vital role in effectively managing …
An intuitionistic approach for the predictability of anti-angiogenic inhibitors in cancer diagnosis
Malignant cancer angiogenesis has historically attracted enormous scientific attention.
Although angiogenesis is requisite for a child's development and conducive to tissue …
Although angiogenesis is requisite for a child's development and conducive to tissue …
Recent advances in multi-criteria decision analysis: A comprehensive review of applications and trends
In recent years, multi-criteria decision support methods have become widely used research
tools by both scientists and practitioners. Theoretical works involving new multi-criteria …
tools by both scientists and practitioners. Theoretical works involving new multi-criteria …
Mathematical assessment of machine learning models used for brain tumor diagnosis
The brain is an intrinsic and complicated component of human anatomy. It is a collection of
connective tissues and nerve cells that regulate the principal actions of the entire body …
connective tissues and nerve cells that regulate the principal actions of the entire body …
Evaluating the performance of deep learning frameworks for malaria parasite detection using microscopic images of peripheral blood smears
Malaria is a significant health concern in many third-world countries, especially for pregnant
women and young children. It accounted for about 229 million cases and 600,000 mortality …
women and young children. It accounted for about 229 million cases and 600,000 mortality …
Selection of optimal approach for cardiovascular disease diagnosis under complex intuitionistic fuzzy dynamic environment
D Alghazzawi, M Liaqat, A Razaq, H Alolaiyan… - Mathematics, 2023 - mdpi.com
Cardiovascular disease (CVD) is a leading global health concern. There is a critical need for
accurate and reliable decision-making tools to select the optimal approach for diagnosing …
accurate and reliable decision-making tools to select the optimal approach for diagnosing …
Predictive modeling for breast cancer classification in the context of Bangladeshi patients by use of machine learning approach with explainable AI
Breast cancer has rapidly increased in prevalence in recent years, making it one of the
leading causes of mortality worldwide. Among all cancers, it is by far the most common …
leading causes of mortality worldwide. Among all cancers, it is by far the most common …
Development of a Novel Multi-Modal Contextual Fusion Model for Early Detection of Varicella Zoster Virus Skin Lesions in Human Subjects
Skin lesion detection is crucial in diagnosing and managing dermatological conditions. In
this study, we developed and demonstrated the potential applicability of a novel mixed-scale …
this study, we developed and demonstrated the potential applicability of a novel mixed-scale …