Information Technology

The revolution of metaverse in surgery: a mini-review with video.

The virtual reality (VR) is an application in which people can interact each other with their own av...

Machine learning characterization of a rare neurologic disease via electronic health records: a proof-of-principle study on stiff person syndrome.

BACKGROUND: Despite the frequent diagnostic delays of rare neurologic diseases (RND), it remains dif...

Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers.

BACKGROUND: Efforts are underway to capitalize on the computational power of the data collected in e...

Innovative approaches in stroke care: insights from recent studies on patient delay, telemedicine, artificial intelligence, and machine learning.

Multimodal deep learning models utilizing chest X-ray and electronic health record data for predictive screening of acute heart failure in emergency department.

BACKGROUND AND OBJECTIVES: Ambiguity in diagnosing acute heart failure (AHF) leads to inappropriate ...

Communicating exploratory unsupervised machine learning analysis in age clustering for paediatric disease.

BACKGROUND: Despite the increasing availability of electronic healthcare record (EHR) data and wide ...

Evaluating the effectiveness of a sliding window technique in machine learning models for mortality prediction in ICU cardiac arrest patients.

Extensive research has been devoted to predicting ICU mortality, to assist clinical teams managing c...

Advancements in AI based healthcare techniques with FOCUS ON diagnostic techniques.

Since the past decade, the interest towards more precise and efficient healthcare techniques with sp...

An Innovative Device Based on Human-Machine Interface (HMI) for Powered Wheelchair Control for Neurodegenerative Disease: A Proof-of-Concept.

In the global context, advancements in technology and science have rendered virtual, augmented, and ...

MoCab: A framework for the deployment of machine learning models across health information systems.

BACKGROUND AND OBJECTIVE: Machine learning models are vital for enhancing healthcare services. Howev...

Ethical Challenges and Opportunities in Applying Artificial Intelligence to Cardiovascular Medicine.

Much anticipation surrounds artificial intelligence's (AI) emergence as a promising tool in health c...

Designing medical artificial intelligence systems for global use: focus on interoperability, scalability, and accessibility.

Advances in artificial intelligence (AI) and machine learning systems promise faster, more efficient...

Advancing Medical Imaging Research Through Standardization: The Path to Rapid Development, Rigorous Validation, and Robust Reproducibility.

Artificial intelligence (AI) has made significant advances in radiology. Nonetheless, challenges in ...

Rapid assessment of heavy metal accumulation capability of Sedum alfredii using hyperspectral imaging and deep learning.

Hyperaccumulators are the material basis and key to the phytoremediation of heavy metal contaminated...

Deep learning empowered breast cancer diagnosis: Advancements in detection and classification.

Recent advancements in AI, driven by big data technologies, have reshaped various industries, with a...

European beech spring phenological phase prediction with UAV-derived multispectral indices and machine learning regression.

Acquiring phenological event data is crucial for studying the impacts of climate change on forest dy...

Combining Federated Machine Learning and Qualitative Methods to Investigate Novel Pediatric Asthma Subtypes: Protocol for a Mixed Methods Study.

BACKGROUND: Pediatric asthma is a heterogeneous disease; however, current characterizations of its s...

Revolutionizing urogynecology: Machine learning application with patient-centric technology: Promise, challenges, and future directions.

In an epoch where digital innovation is redefining the medical landscape, electronic health records ...

Validation of an Electronic Health Record-Based Machine Learning Model Compared With Clinical Risk Scores for Gastrointestinal Bleeding.

BACKGROUND & AIMS: Guidelines recommend use of risk stratification scores for patients presenting wi...

Prospective Randomized Study on the Use of Robot-Assisted Postoperative Visits.

Robot-assisted visits, as part of telemedicine, can offer doctors the opportunity to take care of p...

Estimating the prevalence of diabetic retinopathy in electronic health records with massive missing labels.

OBJECTIVE: The paper aims to address the problem of massive unlabeled patients in electronic health ...