Artificial intelligence based medical decision support system for early and accurate breast cancer prediction

LK Singh, M Khanna, R Singh - Advances in engineering software, 2023 - Elsevier
Feature selection, which picks the optimal subset of characteristics related to the target data
by deleting unnecessary data, is one of the most important aspects of the machine learning …

Computational intelligence in cancer diagnostics: a contemporary review of smart phone apps, current problems, and future research potentials

S Jain, D Naicker, R Raj, V Patel, YC Hu, K Srinivasan… - Diagnostics, 2023 - mdpi.com
Cancer is a dangerous and sometimes life-threatening disease that can have several
negative consequences for the body, is a leading cause of mortality, and is becoming …

A comprehensive analysis on detecting chronic kidney disease by employing machine learning algorithms

MM Nishat, F Faisal, RR Dip… - … on Pervasive Health …, 2021 - publications.eai.eu
Abstract INTRODUCTION: Chronic Kidney Disease refers to the slow, progressive
deterioration of kidney functions. However, the impairment is irreversible and imperceptible …

Optimized stacking ensemble learning model for breast cancer detection and classification using machine learning

M Kumar, S Singhal, S Shekhar, B Sharma… - Sustainability, 2022 - mdpi.com
Breast cancer is the most frequently encountered medical hazard for women in their forties,
affecting one in every eight women. It is the greatest cause of death worldwide, and early …

Integrating metaheuristics and artificial intelligence for healthcare: basics, challenging and future directions

EH Houssein, E Saber, AA Ali, YM Wazery - Artificial Intelligence Review, 2024 - Springer
Accurate and rapid disease detection is necessary to manage health problems early. Rapid
increases in data amount and dimensionality caused challenges in many disciplines, with …

A novel enhanced hybrid clinical decision support system for accurate breast cancer prediction

LK Singh, M Khanna - Measurement, 2023 - Elsevier
Feature selection is one of the crucial data preprocessing techniques for improving the
performance of machine learning (ML) models. Recently, metaheuristic feature selection …

Performance analysis of machine learning algorithms for thyroid disease

H Abbad Ur Rehman, CY Lin, Z Mushtaq… - Arabian Journal for …, 2021 - Springer
Thyroid disease arises from an anomalous growth of thyroid tissue at the verge of the thyroid
gland. Thyroid disorderliness normally ensues when this gland releases abnormal amounts …

A hybrid supervised machine learning classifier system for breast cancer prognosis using feature selection and data imbalance handling approaches

YS Solanki, P Chakrabarti, M Jasinski, Z Leonowicz… - Electronics, 2021 - mdpi.com
Nowadays, breast cancer is the most frequent cancer among women. Early detection is a
critical issue that can be effectively achieved by machine learning (ML) techniques. Thus in …

Optimizing gene selection and cancer classification with hybrid sine cosine and cuckoo search algorithm

A Yaqoob, NK Verma, RM Aziz - Journal of Medical Systems, 2024 - Springer
Gene expression datasets offer a wide range of information about various biological
processes. However, it is difficult to find the important genes among the high-dimensional …

[HTML][HTML] Evaluation of deep learning models for detecting breast cancer using histopathological mammograms Images

S Mohapatra, S Muduly, S Mohanty… - Sustainable Operations …, 2022 - Elsevier
Breast cancer detection based on the deep learning approach has gained much interest
among other conventional-based CAD systems as the conventional based CAD system's …