Artificial intelligence in dermatology image analysis: current developments and future trends
Z Li, KC Koban, TL Schenck, RE Giunta, Q Li… - Journal of clinical …, 2022 - mdpi.com
Background: Thanks to the rapid development of computer-based systems and deep-
learning-based algorithms, artificial intelligence (AI) has long been integrated into the …
learning-based algorithms, artificial intelligence (AI) has long been integrated into the …
Machine learning-based coronary artery disease diagnosis: A comprehensive review
Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and often
leads to a heart attack. It annually causes millions of deaths and billions of dollars in …
leads to a heart attack. It annually causes millions of deaths and billions of dollars in …
Fuzzy-based hunger games search algorithm for global optimization and feature selection using medical data
Feature selection (FS) is one of the basic data preprocessing steps in data mining and
machine learning. It is used to reduce feature size and increase model generalization. In …
machine learning. It is used to reduce feature size and increase model generalization. In …
Artificial intelligence in clinical decision support: a focused literature survey
Objectives: This survey analyses the latest literature contributions to clinical decision support
systems (DSSs) on a two-year period (2017-2018), focusing on the approaches that adopt …
systems (DSSs) on a two-year period (2017-2018), focusing on the approaches that adopt …
Risk prediction of cardiovascular disease using machine learning classifiers
Cardiovascular disease (CVD) makes our heart and blood vessels dysfunctional and often
leads to death or physical paralysis. Therefore, early and automatic detection of CVD can …
leads to death or physical paralysis. Therefore, early and automatic detection of CVD can …
Multi-level impacts of climate change and supply disruption events on a potato supply chain: An agent-based modeling approach
CONTEXT The world is experiencing frequent extreme weather events like droughts,
snowstorms, and shifting of seasons due to climate change. Increased frequency and …
snowstorms, and shifting of seasons due to climate change. Increased frequency and …
Systematic review of machine learning for diagnosis and prognosis in dermatology
K Thomsen, L Iversen, TL Titlestad… - Journal of …, 2020 - Taylor & Francis
Background: Software systems using artificial intelligence for medical purposes have been
developed in recent years. The success of deep neural networks (DNN) in 2012 in the …
developed in recent years. The success of deep neural networks (DNN) in 2012 in the …
Prognosis prediction in traumatic brain injury patients using machine learning algorithms
Predicting treatment outcomes in traumatic brain injury (TBI) patients is challenging
worldwide. The present study aimed to achieve the most accurate machine learning (ML) …
worldwide. The present study aimed to achieve the most accurate machine learning (ML) …
Towards an adapted PHM approach: Data quality requirements methodology for fault detection applications
N Omri, Z Al Masry, N Mairot, S Giampiccolo… - Computers in …, 2021 - Elsevier
Increasingly, extracting knowledge from data has become an important task in organizations
for performance improvements. To accomplish this task, data-driven Prognostics and Health …
for performance improvements. To accomplish this task, data-driven Prognostics and Health …
Machine learning based computer aided diagnosis of breast cancer utilizing anthropometric and clinical features
Breast cancer is one of the most prevalent types of cancers in females, which has become
rampant all over the world in recent years. The survival rate of breast cancer patients …
rampant all over the world in recent years. The survival rate of breast cancer patients …