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Materias / palabras clave: Ciencias médicas; Ciencias de la información; Medical informatics; Cuba; Ciencias medicas; Informacion

The rapid expansion of conversational artificial intelligence (AI) usage in healthcare, nutrition, and digital health education has made prompting a routine part of professional and personal practice. However, each AI pr...

Materias / palabras clave: Medicine: Medicine (General): Computer applications to medicine. Medical informatics

Materias / palabras clave: Medicine: Medicine (General): Computer applications to medicine. Medical informatics; Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry: Neurology. Diseases of the nervous system

Background Large language models (LLMs) have demonstrated promising capabilities in medical diagnostic reasoning, yet their performance in specialized clinical domains such as rheumatology remains incompletely characteri...

Abstract Chronic wounds represent a longstanding clinical problem due to impaired angiogenesis due to insufficient activation of vascular endothelial growth factor receptor 2 (VEGFR2). In this investigation, we used comp...

Abstract Background Thalassemia is the most prevalent single-gene disorder in Sri Lanka, imposing a significant socioeconomic and healthcare burden. Early carrier detection is essential for genetic counselling and the pr...

ObjectivesThis research aims to engineer a specialized, high-speed database architecture tailored for intelligent video surveillance in critical healthcare environments. The primary objective is to overcome the input/out...

Abstract Clinical text de-identification enables the use of electronic health records while protecting patient privacy, but public training data remain scarce and often have mismatched documentation styles. Recent works ...

The huge rise in the number of medical images has caused a major problem in radiology departments. Radiologists are now working harder than ever, which affects the quality of their diagnoses and patient care. It takes 15...

Abstract Background In biomedical research, subjects and biospecimens are commonly tracked using simple IDs or UUIDs, which guarantee uniqueness but convey no embedded semantic information. Contextual metadata (such as t...

BackgroundPredicting enterocutaneous fistula (ECF)–associated sepsis and mortality poses significant challenges in digital health care due to the disease’s complexity and heterogeneous clinical manifestations. Curren...

Abstract Background Malnutrition among hospitalized older adults in the United States is a growing public health concern associated with poor quality of life, increased mortality, higher readmission rates, and loss of in...

Abstract BackgroundMedlinePlus, developed by the National Library of Medicine (NLM) in the United States, is one of the most widely used, authoritative, consumer-grade health information resources on the web....

Abstract Background In China, the informed consent for thrombolysis in patients with AIS tends to be primarily signed by proxy decision-makers, generally for the family members of patients. The decision-making process is...

Diabetes is prevalent globally, expected to increase in the next few years. This includes people with different types of diabetes including type 1 diabetes and type 2 diabetes. There are several causes for the increase: ...

Objectives Medical device calibration underpins accuracy, precision, and reliability, which are critical to optimal device performance and quality healthcare delivery. Despite its importance, little empirical evidence ex...

Abstract Background Tuberculous pericardial effusion (TPE) presents significant diagnostic challenges due to its nonspecific clinical presentation and similarities with other types of pericardial effusion. The available ...

Abstract Purpose MELD Graph is a state-of-the-art artificial intelligence (AI) model for automated detection of focal cortical dysplasia (FCD), but its performance remains limited, highlighting the need to investigate wh...

Abstract Background Chronic conditions cause millions of deaths annually worldwide. Remote patient monitoring using wearable devices and sensors, combined with machine learning (ML), offers promising strategies for disea...

Medical image prediction plays a very significant role in clinical decision-making and early detection and diagnosis of different diseases. However, the quality of medical images has a huge impact on the predictive model...

Sophia E Yu,1 Diep Tran,1 Dingfen Han,2 Cindy X Cai1,3 1Wilmer Eye Institute, Johns Hopkins School of Medicine, Baltimore, MD, USA; 2Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA; 3Biomedic...

The need for early and precise identification of abnormalities has made the detection and classification of brain tumours essential components of medical diagnosis. Because brain tumours are naturally complex and can hav...

This study provides a quantitative framework for wellbeing outcome prediction through intentional cognitive pattern alteration. We demonstrated 81.67% accurate prediction of wellbeing states, in a three-level classificat...