Latest AI and machine learning research in information technology for healthcare professionals.
Alzheimer's disease (AD) patients admitted to intensive care units (ICUs) exhibit varying survival outcomes due to the unique challenges in managing AD patients. Stratifying patient mortality risk and understanding the criticality of nursing care are important to improve the clinical outcomes of AD patients. This study aimed to leverage machine learning (ML) and electronic health records (EHRs) on...
Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine Learning. Despite a well-established mathematical foundation for neural dynamics, there exists numerous software and hardware solutions and stacks whose variability makes it difficult to reproduce findings. Here, we est...
BACKGROUND: The current study sets out to develop and validate a robust machine-learning model utilizing electronic health records (EHR) to forecast t...
This study investigates the efficacy of machine learning models for intrusion detection in the Internet of Medical Things, aiming to enhance cybersecu...
In an era marked by pervasive digital connectivity, cybersecurity concerns have escalated. The rapid evolution of technology has led to a spectrum of ...
OBJECTIVES: Monitoring seizure control metrics is key to clinical care of patients with epilepsy. Manually abstracting these metrics from unstructured...
PURPOSE: Healthcare systems around the world are increasingly facing severe challenges due to problems such as staff shortage, changing demographics a...
The field of ophthalmology is rapidly advancing, with technological innovations enhancing the diagnosis and management of eye diseases. Tele-ophthalmo...
The emergence of telemedicine and artificial intelligence (AI) has set the stage for a possible revolution in the future of medicine and neurology inc...
Automatic disease progression prediction models require large amounts of training data, which are seldom available, especially when it comes to rare d...
Ontologies and terminologies serve as the backbone of knowledge representation in biomedical domains, facilitating data integration, interoperability,...
Generative Artificial Intelligence (GenAI) are algorithms capable of generating original content. The ability of GenAI to learn and generate novel out...
Can Electronic Health Records (EHR) predict opioid misuse in general patient populations? This research trained three backpropagation neural networks ...
The informal settlements of Nairobi have higher neonatal and infant mortality rates than the average for Nairobi. Universal access to important diagno...
Current research in nephrology is increasingly focused on elucidating the complexity inherent in tightly interwoven molecular systems and their correl...
Clinical informatics, which combines health information technology and clinical expertise, aims to improve health care delivery and outcomes. For cand...
Digital health is significantly transforming stroke care, particularly in remote and economically diverse regions, by harnessing mobile and wireless t...
A large language model (LLM) is an artificial intelligence (AI) model that uses natural language processing (NLP) to understand, interpret, and genera...
Natural Language Processing (NLP) is a subset of artificial intelligence that enables machines to understand and respond to human language through Lar...
Learning electronic health records (EHRs) has received emerging attention because of its capability to facilitate accurate medical diagnosis. Since th...