AIMC Topic: Pilot Projects

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Simultaneous detection of dental caries and fissure sealant in intraoral photos by deep learning: a pilot study.

BMC oral health
BACKGROUND: Deep learning, as an artificial intelligence method has been proved to be powerful in analyzing images. The purpose of this study is to construct a deep learning-based model (ToothNet) for the simultaneous detection of dental caries and f...

Machine Learning to Predict Outcomes of Fetal Cardiac Disease: A Pilot Study.

Pediatric cardiology
Prediction of outcomes following a prenatal diagnosis of congenital heart disease (CHD) is challenging. Machine learning (ML) algorithms may be used to reduce clinical uncertainty and improve prognostic accuracy. We performed a pilot study to train M...

Diagnostic biomarker discovery from brain EEG data using LSTM, reservoir-SNN, and NeuCube methods in a pilot study comparing epilepsy and migraine.

Scientific reports
The study introduces a new online spike encoding algorithm for spiking neural networks (SNN) and suggests new methods for learning and identifying diagnostic biomarkers using three prominent deep learning neural network models: deep BiLSTM, reservoir...

Assessment of changes in vessel area during needle manipulation in microvascular anastomosis using a deep learning-based semantic segmentation algorithm: A pilot study.

Neurosurgical review
Appropriate needle manipulation to avoid abrupt deformation of fragile vessels is a critical determinant of the success of microvascular anastomosis. However, no study has yet evaluated the area changes in surgical objects using surgical videos. The ...

Predictive Models for Suicide Attempts in Major Depressive Disorder and the Contribution of : A Pilot Integrative Machine Learning Study.

Depression and anxiety
Suicide is a major public health problem caused by a complex interaction of various factors. Major depressive disorder (MDD) is the most prevalent psychiatric disorder associated with suicide; therefore, it is essential to prioritize suicide predicti...

Unlocking the future of patient Education: ChatGPT vs. LexiComp® as sources of patient education materials.

Journal of the American Pharmacists Association : JAPhA
BACKGROUND: ChatGPT is a conversational artificial intelligence technology that has shown application in various facets of healthcare. With the increased use of AI, it is imperative to assess the accuracy and comprehensibility of AI platforms.

Exploring dental professionals' outlook on the future of dental care amidst the integration of artificial intelligence in dentistry: a pilot study in Pakistan.

BMC oral health
OBJECTIVE: The purpose of this study is to explore the perspectives, familiarity, and readiness of dental faculty members regarding the integration and application of artificial intelligence (AI) in dentistry, with a focus on the possible effects on ...

A Pilot, Predictive Surveillance Model in Pharmacovigilance Using Machine Learning Approaches.

Advances in therapy
INTRODUCTION: The identification of a new adverse event (AE) caused by a drug product is one of the key activities in the pharmaceutical industry to ensure the safety profile of a drug product. Machine learning (ML) has the potential to assist with s...

A comprehensive assessment of machine learning algorithms for enhanced characterization and prediction in orodispersible film development.

International journal of pharmaceutics
Orodispersible films (ODFs) have emerged as innovative pharmaceutical dosage forms, offering patient-specific treatment through adjustable dosing and the combination of diverse active ingredients. This expanding field generates vast datasets, requiri...