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Deep learning approach for tooth numbering and restoration detection on pediatric periapical radiographs in mixed dentition.

Clinical oral investigations
OBJECTIVES: Accurate tooth numbering and restoration detection on periapical radiographs in mixed dentition are critical to the treatment planning process. They also improve the speed and accuracy of treatment processes by automating the early diagno...

Segmenting beyond the imaging data: creation of anatomically valid edentulous mandibular geometries for surgical planning using artificial intelligence.

Clinical oral investigations
BACKGROUND AND OBJECTIVES: Mandibular reconstruction following continuity resection due to tumor ablation or osteonecrosis remains a significant challenge in maxillofacial surgery. Virtual surgical planning (VSP) relies on accurate segmentation of th...

Distinct electroencephalogram microstate in patients with methamphetamine use disorder and obsessive-compulsive disorder.

Journal of affective disorders
BACKGROUND: Electroencephalogram (EEG) microstates reflect momentary localized brain activity and may indicate spontaneous fluctuations within large-scale neural networks. Methamphetamine use disorder (MUD) and obsessive-compulsive disorder (OCD) exh...

Multifactorial Biomarkers for "Talk and Deteriorate" after Head Trauma Identified Using Machine Learning.

Neurologia medico-chirurgica
Talk and Deteriorate refers to a clinical course where a patient is able to speak immediately after a traumatic brain injury but subsequently deteriorates in consciousness. Talk and Deteriorate outcomes are poor, and reliable prediction may help impr...

Comparative analysis of robotic assisted vs. traditional spinal angiography in a large single-center experience.

Journal of the neurological sciences
BACKGROUND: Spinal angiography (SA) remains the gold standard for evaluating spinal cord vasculature, but traditional approaches expose operators and patients to significant ionizing radiation. Robotic-assisted platforms offer potential advantages th...

Using machine learning models to predict vaccine hesitancy: a showcase of COVID-19 vaccine hesitancy in rural populations during the pandemic.

Vaccine
Understanding vaccine hesitancy is a critical public health challenge, yet traditional statistical methods often fail to capture the complex drivers behind it. This study uses COVID-19 vaccine hesitancy in a rural population as a case study to demons...

Machine Learning Models to Predict Withdrawal of Life-Sustaining Therapy in Patients With Severe Traumatic Brain Injury.

Neurology
BACKGROUND AND OBJECTIVES: Over half of all deaths after traumatic brain injury (TBI) follow the decision to withdraw life-sustaining therapy (WLST). Despite recent improvements in TBI mortality, rates of WLST have remained unchanged, potentially ref...

Decoding IBD progression: a dynamic biomarker atlas for personalized disease stratification.

Journal of translational medicine
BACKGROUND: Accurate staging is pivotal for tailoring treatment intensity, optimizing resource allocation, and improving long-term patient outcomes in IBD. The intestinal microbiota and transcriptional profiles emerge as critical determinants in IBD ...

Effect of artificial intelligence-assisted personalized feedback on radiographic diagnostic performance of dental students: a controlled study.

BMC medical education
BACKGROUND: This study aimed to evaluate the impact of MeSH based personalized learning guides generated by ChatGPT-4o on the radiographic diagnostic performance of dental students and to compare it with the traditional correct/incorrect feedback met...

Machine learning-based integration of pericoronary adipose tissue and clinical risk factors for cardiovascular risk prediction in type 2 diabetes: a retrospective cohort study.

European journal of medical research
BACKGROUND: Cardiovascular disease remains the predominant cause of morbidity and mortality in individuals with type 2 diabetes mellitus (T2DM). Traditional risk models are limited in predictive accuracy. Pericoronary adipose tissue (PCAT), a novel i...