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Prospective Studies

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Use of Hearing Aids Embedded with Inertial Sensors and Artificial Intelligence to Identify Patients at Risk for Falling.

Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
OBJECTIVE: To compare fall risk scores of hearing aids embedded with inertial measurement units (IMU-HAs) and powered by artificial intelligence (AI) algorithms with scores by trained observers.

Predicting grip strength-related frailty in middle-aged and older Chinese adults using interpretable machine learning models: a prospective cohort study.

Frontiers in public health
INTRODUCTION: Frailty is an emerging global health burden, and there is no consensus on the precise prediction of frailty. We aimed to explore the association between grip strength and frailty and interpret the optimal machine learning (ML) model usi...

Utility of an Echocardiographic Machine Learning Model to Predict Outcomes in Intensive Cardiac Care Unit Patients.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
INTRODUCTION: The risk stratification at admission to the intensive cardiac care unit (ICCU) is crucial and remains challenging.

Deep learning for segmentation of colorectal carcinomas on endoscopic ultrasound.

Techniques in coloproctology
BACKGROUND: Bowel-preserving local resection of early rectal cancer is less successful if the tumor infiltrates the muscularis propria as opposed to submucosal infiltration only. Magnetic resonance imaging currently lacks the spatial resolution to pr...

A clinical practical model for preoperative prediction of visual outcome for pituitary adenoma patients in a retrospective and prospective study.

Frontiers in endocrinology
OBJECTIVE: Preoperative prediction of visual recovery after pituitary adenoma resection surgery remains challenging. This study aimed to investigate the value of clinical and radiological features in preoperatively predicting visual outcomes after su...

Performance of image processing analysis and a deep convolutional neural network for the classification of oral cancer in fluorescence visualization.

International journal of oral and maxillofacial surgery
The aim of this prospective study was to determine the effectiveness of screening using image processing analysis and a deep convolutional neural network (DCNN) to classify oral cancers using non-invasive fluorescence visualization. The study include...

Prospective Evaluation of Real-Time Artificial Intelligence for the Hill Classification of the Gastroesophageal Junction.

United European gastroenterology journal
BACKGROUND: Assessment of the gastroesophageal junction (GEJ) is an integral part of gastroscopy; however, the absence of standardized reporting hinders consistency of examination documentation. The Hill classification offers a standardized approach ...

Employing artificial intelligence for optimising antibiotic dosages in sepsis on intensive care unit: a study protocol for a prospective observational study (KI.SEP).

BMJ open
INTRODUCTION: In sepsis treatment, achieving and maintaining effective antibiotic therapy is crucial. However, optimal antibiotic dosing faces challenges due to significant variability among patients with sepsis. Therapeutic drug monitoring (TDM), th...

Wound imaging software and digital platform to assist review of surgical wounds using patient smartphones: The development and evaluation of artificial intelligence (WISDOM AI study).

PloS one
INTRODUCTION: Surgical patients frequently experience post-operative complications at home. Digital remote monitoring of surgical wounds via image-based systems has emerged as a promising solution for early detection and intervention. However, the in...