AIMC Topic: Adult

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Artificial intelligence and the future of psychiatry: Insights from a global physician survey.

Artificial intelligence in medicine
BACKGROUND: Futurists have predicted that new autonomous technologies, embedded with artificial intelligence (AI) and machine learning (ML), will lead to substantial job losses in many sectors disrupting many aspects of healthcare. Mental health appe...

Diagnosis of cystic lesions using panoramic and cone beam computed tomographic images based on deep learning neural network.

Oral diseases
OBJECTIVES: The aim of the current study was to evaluate the detection and diagnosis of three types of odontogenic cystic lesions (OCLs)-odontogenic keratocysts, dentigerous cysts, and periapical cysts-using dental panoramic radiography and cone beam...

Implementing machine learning in bipolar diagnosis in China.

Translational psychiatry
Bipolar disorder (BPD) is often confused with major depression, and current diagnostic questionnaires are subjective and time intensive. The aim of this study was to develop a new Bipolar Diagnosis Checklist in Chinese (BDCC) by using machine learnin...

Prediction of fetal weight at varying gestational age in the absence of ultrasound examination using ensemble learning.

Artificial intelligence in medicine
Obstetric ultrasound examination of physiological parameters has been mainly used to estimate the fetal weight during pregnancy and baby weight before labour to monitor fetal growth and reduce prenatal morbidity and mortality. However, the problem is...

Muscle endurance time estimation during isometric training using electromyogram and supervised learning.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
UNLABELLED: Constant-force isometric muscle training is useful for increasing the maximal strength , rehabilitation and work-fatigue assessment. Earlier studies have shown that muscle fatigue characteristics can be used for evaluating muscle enduranc...

Abstract art paintings, global image properties, and verbal descriptions: An empirical and computational investigation.

Acta psychologica
While global image properties (GIPs) relate to preference ratings in many categories of visual stimuli, this relationship is typically not seen for abstract art paintings. Using computational network science and empirical methods, we further investig...

Detecting liver fibrosis using a machine learning-based approach to the quantification of the heart-induced deformation in tagged MR images.

NMR in biomedicine
Liver disease causes millions of deaths per year worldwide, and approximately half of these cases are due to cirrhosis, which is an advanced stage of liver fibrosis that can be accompanied by liver failure and portal hypertension. Early detection of ...

Triaging ophthalmology outpatient referrals with machine learning: A pilot study.

Clinical & experimental ophthalmology
IMPORTANCE: Triaging of outpatient referrals to ophthalmology services is required for the maintenance of patient care and appropriate resource allocation. Machine learning (ML), in particular natural language processing, may be able to assist with t...

Volumetry of Mesiotemporal Structures Reflects Serostatus in Patients with Limbic Encephalitis.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Limbic encephalitis is an autoimmune disease. A variety of autoantibodies have been associated with different subtypes of limbic encephalitis, whereas its MR imaging signature is uniformly characterized by mesiotemporal abnorm...

Predicting O-Water PET cerebral blood flow maps from multi-contrast MRI using a deep convolutional neural network with evaluation of training cohort bias.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
To improve the quality of MRI-based cerebral blood flow (CBF) measurements, a deep convolutional neural network (dCNN) was trained to combine single- and multi-delay arterial spin labeling (ASL) and structural images to predict gold-standard O-water ...