Impact of AI-powered solutions in rehabilitation process: Recent improvements and future trends
Rehabilitation is an important and necessary part of local and global healthcare services
along with treatment and palliative care, prevention of disease, and promotion of good …
along with treatment and palliative care, prevention of disease, and promotion of good …
[HTML][HTML] Defining a metric-driven approach for learning hazardous situations
Artificial intelligence has brought many innovations to our lives. At the same time, it is worth
designing robust safety machine learning (ML) algorithms to obtain more benefits from …
designing robust safety machine learning (ML) algorithms to obtain more benefits from …
An ai-empowered infrastructure for risk prevention during medical examination
A medical examination at Nuclear Medicine Department (NMD) carries out at multiple
stages. Patients are accompanied and guided by nurses during their movements within the …
stages. Patients are accompanied and guided by nurses during their movements within the …
[HTML][HTML] Enhancing Diagnostic Accuracy for Skin Cancer and COVID-19 Detection: A Comparative Study Using a Stacked Ensemble Method
In recent years, COVID-19 and skin cancer have become two prevalent illnesses with severe
consequences if untreated. This research represents a significant step toward leveraging …
consequences if untreated. This research represents a significant step toward leveraging …
ERLNEIL-MDP: Evolutionary reinforcement learning with novelty-driven exploration for medical data processing
The rapid growth of medical data presents opportunities and challenges for healthcare
professionals and researchers. To effectively process and analyze this complex and …
professionals and researchers. To effectively process and analyze this complex and …
Smart Imitator: Learning from Imperfect Clinical Decisions
Abstract Objectives This study introduces Smart Imitator (SI), a 2-phase reinforcement
learning (RL) solution enhancing personalized treatment policies in healthcare, addressing …
learning (RL) solution enhancing personalized treatment policies in healthcare, addressing …
Cloud-based monitoring system for personalized home medication
This paper introduces an Artificial Intelligence (AI)-enabled system to assist patients to follow
a treatment plan at home. The deep learning model is a Convolutional Neural Network …
a treatment plan at home. The deep learning model is a Convolutional Neural Network …
Enhancing Medical Training through Learning from Mistakes by Interacting with an Ill-trained Reinforcement Learning Agent
This article presents a 3-D medical simulation that employs reinforcement learning (RL) and
interactive RL (IRL) to teach and assess the procedure of donning and doffing personal …
interactive RL (IRL) to teach and assess the procedure of donning and doffing personal …
Reinforced Sequential Decision-Making for Sepsis Treatment: The PosNegDM Framework with Mortality Classifier and Transformer
Sepsis, a life-threatening condition triggered by the body's exaggerated response to
infection, demands urgent intervention to prevent severe complications. Existing machine …
infection, demands urgent intervention to prevent severe complications. Existing machine …
[HTML][HTML] Advancing Patient Care with an Intelligent and Personalized Medication Engagement System
Therapeutic efficacy is affected by adherence failure as also demonstrated by WHO clinical
studies that 50–70% of patients follow a treatment plan properly. Patients' failure to follow …
studies that 50–70% of patients follow a treatment plan properly. Patients' failure to follow …