Latest AI and machine learning research in surveys for healthcare professionals.
This paper presents a unified model for combining beamforming and blind source separation (BSS). The validity of the model's assumptions is confirmed by recovering target speech information in noise accurately using Oracle information. Using real static human-robot interaction (HRI) data, the proposed combination of BSS with the minimum-variance distortionless response beamformer provides a greate...
OBJECTIVE: Preterm infants are at high risk of neuromotor disorders. Recent advances in digital technology and machine learning algorithms have enabled the tracking and recognition of anatomical key points of the human body. It remains unclear whether the proposed pose estimation model and the skeleton-based action recognition model for adult movement classification are applicable and accurate for...
Advances in machine learning for health care have brought concerns about bias from the research community; specifically, the introduction, perpetuatio...
Artificial intelligence (AI) is increasingly transforming healthcare, however, the interaction between the user, AI, and the user’s environment is poo...
Artificial intelligence (AI) large language models (LLMs) hold great potential to transform psychiatry and mental health care by delivering relevant a...
Diagnostic codes in the Electronic Health Record (EHR) are known to be limited in reporting patient suicidality, and especially in differentiating the...
Implicit bias can impede patient-provider interactions and lead to inequities in care. Raising awareness is key to reducing such bias, but its manifes...
Although clinician-supported computer-assisted cognitive-behaviour therapy (CCBT) is well established as an effective treatment for depression and anx...
To develop and test an NLP algorithm that accurately detects the presence of information reported from DXA scans containing femoral neck T-scores of ...
Mitigation of racism in artificial intelligence (AI) is needed to improve health outcomes, yet no consensus exists on how this might be achieved. At...
Timely detection of disease outbreaks is critical in public health. Artificial Intelligence (AI) can identify patterns in data that signal the onset ...
One potential application of neural networks (NNs) is the early-stage detection of oral cancer. This systematic review aimed to determine the level of...
Purpose To develop an end-to-end deep learning (DL) pipeline for automated ventricular segmentation of cardiac MRI data from a multicenter registry of...
To date, pure-tone audiometry remains the gold standard for clinical auditory testing. However, pure-tone audiometry is time-consuming and only provid...
This study aimed to investigate the accuracy, reliability, and readability of A-Eye Consult, ChatGPT-4.0, Google Gemini and Copilot AI large language...
OBJECTIVES: Digestive endoscopy is an important diagnostic and therapeutic tool for digestive system diseases. The artificial intelligence (AI)-assist...
The aim of this study is to present the first Italian experience with robotic-assisted retrograde intrarenal surgery (rRIRS) using the Ily platform. P...
The American Journal of Occupational Therapy (AJOT) has maintained its top-ranking status in the field of occupational therapy, as evidenced by an inc...
Urban climate model evaluation often remains limited by a lack of trusted urban weather observations. The increasing density of personal weather senso...
BACKGROUND: Incorporating artificial intelligence (AI) into clinics brings the risk of automation bias, which potentially misleads the clinician's dec...