Machine learning in medical applications: A review of state-of-the-art methods
Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …
complex challenges in recent years in various application areas, such as medical, financial …
Evaluation of artificial intelligence techniques in disease diagnosis and prediction
N Ghaffar Nia, E Kaplanoglu, A Nasab - Discover Artificial Intelligence, 2023 - Springer
A broad range of medical diagnoses is based on analyzing disease images obtained
through high-tech digital devices. The application of artificial intelligence (AI) in the …
through high-tech digital devices. The application of artificial intelligence (AI) in the …
Comparison of feature importance measures as explanations for classification models
M Saarela, S Jauhiainen - SN Applied Sciences, 2021 - Springer
Explainable artificial intelligence is an emerging research direction helping the user or
developer of machine learning models understand why models behave the way they do …
developer of machine learning models understand why models behave the way they do …
Machine learning in medicine: a practical introduction
JAM Sidey-Gibbons, CJ Sidey-Gibbons - BMC medical research …, 2019 - Springer
Background Following visible successes on a wide range of predictive tasks, machine
learning techniques are attracting substantial interest from medical researchers and …
learning techniques are attracting substantial interest from medical researchers and …
1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset
G Litjens, P Bandi, B Ehteshami Bejnordi… - …, 2018 - academic.oup.com
Background The presence of lymph node metastases is one of the most important factors in
breast cancer prognosis. The most common way to assess regional lymph node status is the …
breast cancer prognosis. The most common way to assess regional lymph node status is the …
An enhanced grey wolf optimization based feature selection wrapped kernel extreme learning machine for medical diagnosis
In this study, a new predictive framework is proposed by integrating an improved grey wolf
optimization (IGWO) and kernel extreme learning machine (KELM), termed as IGWO‐KELM …
optimization (IGWO) and kernel extreme learning machine (KELM), termed as IGWO‐KELM …
A generalized deep learning framework for whole-slide image segmentation and analysis
Histopathology tissue analysis is considered the gold standard in cancer diagnosis and
prognosis. Whole-slide imaging (WSI), ie, the scanning and digitization of entire histology …
prognosis. Whole-slide imaging (WSI), ie, the scanning and digitization of entire histology …
[图书][B] Convex analysis and global optimization
H Tuy, T Hoang, T Hoang, V Mathématicien, T Hoang… - 1998 - Springer
Optimization has been expanding in all directions at an astonishing rate during the last few
decades. New algorithmic and theoretical techniques have been developed, the diffusion …
decades. New algorithmic and theoretical techniques have been developed, the diffusion …
Breast cancer diagnosis and prognosis via linear programming
OL Mangasarian, WN Street… - Operations …, 1995 - pubsonline.informs.org
Two medical applications of linear programming are described in this paper. Specifically,
linear programming-based machine learning techniques are used to increase the accuracy …
linear programming-based machine learning techniques are used to increase the accuracy …
Breast cancer diagnosis using feature ensemble learning based on stacked sparse autoencoders and softmax regression
Nowadays, the most frequent cancer in women is breast cancer (malignant tumor). If breast
cancer is detected at the beginning stage, it can often be cured. Many researchers proposed …
cancer is detected at the beginning stage, it can often be cured. Many researchers proposed …