AIMC Topic: Adult

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Evaluation of high-resolution pituitary dynamic contrast-enhanced MRI using deep learning-based compressed sensing and super-resolution reconstruction.

European radiology
OBJECTIVE: This study aims to assess diagnostic performance of high-resolution dynamic contrast-enhanced (DCE) MRI with deep learning-based compressed sensing and super-resolution (DLCS-SR) reconstruction for identifying microadenomas.

Opinions and Perspectives of Canadian Occupational Therapists on Artificial Intelligence.

Canadian journal of occupational therapy. Revue canadienne d'ergotherapie
Technology is rapidly being developed to improve healthcare outcomes. However, the attitudes and perceptions of occupational therapists (OTs) on artificial intelligence (AI) in healthcare are not yet known. This study aims to: explore Canadian OTs'...

Longitudinal brain age in first-episode mania youth treated with lithium or quetiapine.

European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
It is unclear if lithium and quetiapine have neuroprotective effects, especially in early stages of bipolar and schizoaffective disorders. Here, an age-related multivariate brain structural measure (i.e., brain-PAD) at baseline and changes in respons...

The differential diagnosis of autism spectrum disorder in adults.

Expert review of neurotherapeutics
INTRODUCTION: Diagnosing autism spectrum disorder (ASD) in adults is challenging due to its heterogeneity and symptom overlap with other conditions. Making an accurate diagnosis can be difficult and overwhelming but is vital for proper accommodations...

The role of patient outcomes in shaping moral responsibility in AI-supported decision making.

Radiography (London, England : 1995)
INTRODUCTION: Integrating decision support mechanisms utilising artificial intelligence (AI) into medical radiation practice introduces unique challenges to accountability for patient care outcomes. AI systems, often seen as "black boxes," can obscur...

Principles for enhancing trust in artificial intelligence systems among medical imaging professionals in Ghana: A nationwide cross-sectional study.

Radiography (London, England : 1995)
INTRODUCTION: To realise the full potential of artificial intelligence (AI) systems in medical imaging, it is crucial to address challenges, such as cyberterrorism to foster trust and acceptance. This study aimed to determine the principles that enha...

Machine learning models for improving the diagnosing efficiency of skeletal class I and III in German orthodontic patients.

Scientific reports
The precise and efficient diagnosis of an individual's skeletal class is necessary in orthodontics to ensure correct and stable treatment planning. However, it is difficult to efficiently determine the true skeletal class due to several correlations ...

Deep learning enabled liquid-based cytology model for cervical precancer and cancer detection.

Nature communications
Deep learning (DL) enabled liquid-based cytology has potential for cervical cancer screening or triage. Here, we develop a DL model using whole cytology slides from 17,397 women and test it on 10,826 additional cases through a three-stage process. Th...

Development of a machine learning-based diagnostic model using hematological parameters to differentiate periductal mastitis from granulomatous lobular mastitis.

Science progress
ObjectiveNonpuerperal mastitis (NPM) is an inflammatory condition, including periductal mastitis (PDM) and granulomatous lobular mastitis (GLM). The clinical manifestations of PDM and GLM are highly similar, posing significant challenges in their dif...

Novel endometrial receptivity test increases clinical pregnancy and live birth rates in patients with recurrent implantation failure: Secondary analysis of a prospective clinical trial.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVES: This study aimed to evaluate the efficiency of endometrial receptivity testing (ERT) in improving pregnancy outcomes for patients with recurrent implantation failure (RIF), and to investigate the incidence of implantation window displacem...