Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine
Precision medicine is one of the recent and powerful developments in medical care, which
has the potential to improve the traditional symptom-driven practice of medicine, allowing …
has the potential to improve the traditional symptom-driven practice of medicine, allowing …
Artificial intelligence and machine learning in precision and genomic medicine
S Quazi - Medical Oncology, 2022 - Springer
The advancement of precision medicine in medical care has led behind the conventional
symptom-driven treatment process by allowing early risk prediction of disease through …
symptom-driven treatment process by allowing early risk prediction of disease through …
[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 …
Ethical considerations about artificial intelligence for prognostication in intensive care
M Beil, I Proft, D Van Heerden, S Sviri… - Intensive care medicine …, 2019 - Springer
Background Prognosticating the course of diseases to inform decision-making is a key
component of intensive care medicine. For several applications in medicine, new methods …
component of intensive care medicine. For several applications in medicine, new methods …
[HTML][HTML] State of the art of machine learning–enabled clinical decision support in intensive care units: literature review
N Hong, C Liu, J Gao, L Han, F Chang… - JMIR medical …, 2022 - medinform.jmir.org
Background Modern clinical care in intensive care units is full of rich data, and machine
learning has great potential to support clinical decision-making. The development of …
learning has great potential to support clinical decision-making. The development of …
COVID-19 scenario modelling for the mitigation of capacity-dependent deaths in intensive care
Managing healthcare demand and capacity is especially difficult in the context of the COVID-
19 pandemic, where limited intensive care resources can be overwhelmed by a large …
19 pandemic, where limited intensive care resources can be overwhelmed by a large …
[PDF][PDF] Incorporating Explainable Artificial Intelligence (XAI) to aid the Understanding of Machine Learning in the Healthcare Domain.
In the healthcare domain, Artificial Intelligence (AI) based systems are being increasingly
adopted with applications ranging from surgical robots to automated medical diagnostics …
adopted with applications ranging from surgical robots to automated medical diagnostics …
Computer-aided diagnosis of COVID-19 from chest x-ray images using hybrid-features and random forest classifier
In recent years, a lot of attention has been paid to using radiology imaging to automatically
find COVID-19.(1) Background: There are now a number of computer-aided diagnostic …
find COVID-19.(1) Background: There are now a number of computer-aided diagnostic …
[HTML][HTML] Modelling and optimization of microhardness of electroless Ni–P–TiO2 composite coating based on machine learning approaches and RSM
In this study, experimental investigations on the microhardness of the synthesized
electroless Ni–P–TiO 2 coated aluminium composite was carried out. The coated samples …
electroless Ni–P–TiO 2 coated aluminium composite was carried out. The coated samples …
Evaluation of patient safety culture using a random forest algorithm
Safety culture is a multidimensional concept that may be associated with medical errors and
patient safety events in healthcare delivery systems. However, limited evidence is available …
patient safety events in healthcare delivery systems. However, limited evidence is available …