[HTML][HTML] Significance of machine learning in healthcare: Features, pillars and applications
Abstract Machine Learning (ML) applications are making a considerable impact on
healthcare. ML is a subtype of Artificial Intelligence (AI) technology that aims to improve the …
healthcare. ML is a subtype of Artificial Intelligence (AI) technology that aims to improve the …
A deep feature learning model for pneumonia detection applying a combination of mRMR feature selection and machine learning models
Pneumonia is one of the diseases that people may encounter in any period of their lives.
Approximately 18% of infectious diseases are caused by pneumonia. This disease may …
Approximately 18% of infectious diseases are caused by pneumonia. This disease may …
Intelligent telehealth in pharmacovigilance: a future perspective
Pharmacovigilance improves patient safety by detecting and preventing adverse drug
events. However, challenges exist that limit adverse drug event detection, resulting in many …
events. However, challenges exist that limit adverse drug event detection, resulting in many …
Review of natural language processing in pharmacology
D Trajanov, V Trajkovski, M Dimitrieva, J Dobreva… - Pharmacological …, 2023 - ASPET
Natural language processing (NLP) is an area of artificial intelligence that applies
information technologies to process the human language, understand it to a certain degree …
information technologies to process the human language, understand it to a certain degree …
Convolutional neural network for discriminating nasopharyngeal carcinoma and benign hyperplasia on MRI
Objectives A convolutional neural network (CNN) was adapted to automatically detect early-
stage nasopharyngeal carcinoma (NPC) and discriminate it from benign hyperplasia on a …
stage nasopharyngeal carcinoma (NPC) and discriminate it from benign hyperplasia on a …
[HTML][HTML] An intelligent multimodal medical diagnosis system based on patients' medical questions and structured symptoms for telemedicine
The massive increase in health-related digital data has revolutionized the power of machine
learning algorithms to produce more salient information. Digital health data consists of …
learning algorithms to produce more salient information. Digital health data consists of …
A statistically rigorous deep neural network approach to predict mortality in trauma patients admitted to the intensive care unit
BACKGROUND Trauma patients admitted to critical care are at high risk of mortality
because of their injuries. Our aim was to develop a machine learning-based model to predict …
because of their injuries. Our aim was to develop a machine learning-based model to predict …
App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning
Background Tests are scarce resources, especially in low and middle-income countries, and
the optimization of testing programs during a pandemic is critical for the effectiveness of the …
the optimization of testing programs during a pandemic is critical for the effectiveness of the …
Predicting infections using computational intelligence–a systematic review
Infections encompass a set of medical conditions of very diverse kinds that can pose a
significant risk to health, and even death. As with many other diseases, early diagnosis can …
significant risk to health, and even death. As with many other diseases, early diagnosis can …
[HTML][HTML] Transforming urinary stone disease management by artificial intelligence-based methods: a comprehensive review
A Anastasiadis, A Koudonas, G Langas… - Asian Journal of …, 2023 - Elsevier
Objective To provide a comprehensive review on the existing research and evidence
regarding artificial intelligence (AI) applications in the assessment and management of …
regarding artificial intelligence (AI) applications in the assessment and management of …