AIMC Topic: Artificial Intelligence

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Improving colorectal cancer screening - consumer-centred technological interventions to enhance engagement and participation amongst diverse cohorts.

Clinics and research in hepatology and gastroenterology
The current "Gold Standard" colorectal cancer (CRC) screening approach of faecal occult blood test (FOBT) with follow-up colonoscopy has been shown to significantly improve morbidity and mortality, by enabling the early detection of disease. However,...

Technical and engineering considerations for designing therapeutics and delivery systems.

Journal of controlled release : official journal of the Controlled Release Society
The newly-emerged pathological conditions and increased rates of drug resistance necessitate application of the state-of-the-art technologies for accelerated discovery of the therapeutic candidates and obtaining comprehensive knowledge about their ta...

Geographical classification of malaria parasites through applying machine learning to whole genome sequence data.

Scientific reports
Malaria, caused by Plasmodium parasites, is a major global health challenge. Whole genome sequencing (WGS) of Plasmodium falciparum and Plasmodium vivax genomes is providing insights into parasite genetic diversity, transmission patterns, and can inf...

Applications of Artificial Intelligence to Obesity Research: Scoping Review of Methodologies.

Journal of medical Internet research
BACKGROUND: Obesity is a leading cause of preventable death worldwide. Artificial intelligence (AI), characterized by machine learning (ML) and deep learning (DL), has become an indispensable tool in obesity research.

Caries detection with tooth surface segmentation on intraoral photographic images using deep learning.

BMC oral health
BACKGROUND: Intraoral photographic images are helpful in the clinical diagnosis of caries. Moreover, the application of artificial intelligence to these images has been attempted consistently. This study aimed to evaluate a deep learning algorithm fo...

A deep learning model based on concatenation approach to predict the time to extract a mandibular third molar tooth.

BMC oral health
BACKGROUND: Assessing the time required for tooth extraction is the most important factor to consider before surgeries. The purpose of this study was to create a practical predictive model for assessing the time to extract the mandibular third molar ...

The impacts of fine-tuning, phylogenetic distance, and sample size on big-data bioacoustics.

PloS one
Vocalizations in animals, particularly birds, are critically important behaviors that influence their reproductive fitness. While recordings of bioacoustic data have been captured and stored in collections for decades, the automated extraction of dat...

Feasibility of a lung airway navigation system using fiber-Bragg shape sensing and artificial intelligence for early diagnosis of lung cancer.

PloS one
Currently early diagnosis of malignant lesions at the periphery of lung parenchyma requires guidance of the biopsy needle catheter from the bronchoscope into the smaller peripheral airways via harmful X-ray radiation. Previously, we developed an imag...

A machine learning approach for predicting perihematomal edema expansion in patients with intracerebral hemorrhage.

European radiology
OBJECTIVES: Preventing the expansion of perihematomal edema (PHE) represents a novel strategy for the improvement of neurological outcomes in intracerebral hemorrhage (ICH) patients. Our goal was to predict early and delayed PHE expansion using a mac...

Prediction of Marathon Performance using Artificial Intelligence.

International journal of sports medicine
Although studies used machine learning algorithms to predict performances in sports activities, none, to the best of our knowledge, have used and validated two artificial intelligence techniques: artificial neural network (ANN) and k-nearest neighbor...