AIMC Topic: Pilot Projects

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Exoskeleton rehabilitation robot training for balance and lower limb function in sub-acute stroke patients: a pilot, randomized controlled trial.

Journal of neuroengineering and rehabilitation
PURPOSE: This pilot study aimed to investigate the effects of REX exoskeleton rehabilitation robot training on the balance and lower limb function in patients with sub-acute stroke.

Assessment of an AI-based tool for population-wide collection of placental morphological data.

European journal of obstetrics, gynecology, and reproductive biology
OBJECTIVES: Automated placental assessment could allow accurate and timely morphological/pathological measurements at scale. We undertook a pilot study using an artificial intelligence-based assessment system (AI-PLAX) to ascertain the potential of a...

Prediction of vitreomacular traction syndrome outcomes with deep learning: A pilot study.

European journal of ophthalmology
PURPOSE: To investigate the potential of an Optical Coherence Tomography (OCT) based Deep-Learning (DL) model in the prediction of Vitreomacular Traction (VMT) syndrome outcomes.

Machine learning-based preoperative analytics for the prediction of anastomotic leakage in colorectal surgery: a swiss pilot study.

Surgical endoscopy
BACKGROUND: Anastomotic leakage (AL), a severe complication following colorectal surgery, arises from defects at the anastomosis site. This study evaluates the feasibility of predicting AL using machine learning (ML) algorithms based on preoperative ...

Testing the generalizability and effectiveness of deep learning models among clinics: sperm detection as a pilot study.

Reproductive biology and endocrinology : RB&E
BACKGROUND: Deep learning has been increasingly investigated for assisting clinical in vitro fertilization (IVF). The first technical step in many tasks is to visually detect and locate sperm, oocytes, and embryos in images. For clinical deployment o...

Pilot-Study to Explore Metabolic Signature of Type 2 Diabetes: A Pipeline of Tree-Based Machine Learning and Bioinformatics Techniques for Biomarkers Discovery.

Nutrients
BACKGROUND: This study aims to identify unique metabolomics biomarkers associated with Type 2 Diabetes (T2D) and develop an accurate diagnostics model using tree-based machine learning (ML) algorithms integrated with bioinformatics techniques.

Using Artificial Intelligence to Improve the Accuracy of a Wrist-Worn, Noninvasive Glucose Monitor: A Pilot Study.

Journal of diabetes science and technology
BACKGROUND: Self-monitoring of glucose is important to the successful management of diabetes; however, existing monitoring methods require a degree of invasive measurement which can be unpleasant for users. This study investigates the accuracy of a n...

Deep learning for determining the difficulty of endodontic treatment: a pilot study.

BMC oral health
BACKGROUND: To develop and validate a deep learning model for automated assessment of endodontic case difficulty from periapical radiographs.