Identifying disease and diagnosis in females using machine learning

S Pramanik, SK Bandyopadhyay - Encyclopedia of Data Science …, 2023 - igi-global.com
Here, the researchers are trying to prepare a model for identifying whether a patient is
diabetic or not. The Pima Indian Dataset has been used in this case study. There are two …

Breast cancer detection based on modified Harris Hawks optimization and extreme learning machine embedded with feature weighting

F Jiang, Q Zhu, T Tian - Neural Processing Letters, 2023 - Springer
Computer-aided diagnosis (CAD) can assist doctors with clinical diagnosis and improve
diagnosis accuracy and efficiency further. It is significative and valuable for cancer detection …

Dense convolutional neural network based deep learning framework for the diagnosis of breast cancer

H Kaur - Wireless Personal Communications, 2023 - Springer
Breast Cancer is second most deadly disease prevailing among women after lung cancer.
Females affected with breast cancer are vulnerable to grave health-related issues with a …

Design and development of an intelligent system for predicting 5-year survival in gastric cancer

MR Afrash, M Shanbehzadeh… - Clinical Medicine …, 2022 - journals.sagepub.com
Background: Gastric cancer remains one of the leading causes of worldwide cancer-specific
deaths. Accurately predicting the survival likelihood of gastric cancer patients can inform …

Using explainable machine learning to explore the impact of synoptic reporting on prostate cancer

FM Janssen, KKH Aben, BL Heesterman… - Algorithms, 2022 - mdpi.com
Machine learning (ML) models have proven to be an attractive alternative to traditional
statistical methods in oncology. However, they are often regarded as black boxes, hindering …

Extreme gradient boosting and soft voting ensemble classifier for diabetes prediction

DK Behera, S Dash, AK Behera… - 2021 19th OITS …, 2021 - ieeexplore.ieee.org
Diabetes is a chronic disease that has been impacting an increasing number of people
throughout the years. Each year, it results in a huge number of deaths. Due to the fact that …

Prediction of Breast cancer using integrated machine learning-fuzzy and dimension reduction techniques

S Prusty, P Das, SK Dash, S Patnaik… - Journal of Intelligent …, 2023 - content.iospress.com
In the last two decades, regardless of epidemiological, and clinical studies, the incidence of
breast cancer (BC) is still increasing. However, so far, a lot of research has been done in this …

Unique clusters of patterns of breast cancer survivorship

HI Okagbue, PE Oguntunde, PI Adamu… - Health and …, 2022 - Springer
This research focused on analyzing and classifying the survival of some breast cancer in-
patients in Kwara State, Nigeria. The relationships between some variables that were …

Single-label machine learning classification revealed some hidden but inter-related causes of five psychotic disorder diseases

HI Okagbue, OA Ijezie, PO Ugwoke… - Heliyon, 2023 - cell.com
Psychotic disorder diseases (PDD) or mental illnesses are group of illnesses that affect the
minds and impair the cognitive ability, retard emotional ability and obstruct the process of …

Iterative tuning of tree-ensemble-based models' parameters using Bayesian optimization for breast cancer prediction

A Alsabry, M Algabri - Информатика и автоматизация, 2024 - mathnet.ru
The study presents a method for iterative parameter tuning of tree ensemble-based models
using Bayesian hyperparameter tuning for states prediction, using breast cancer as an …