Eating Disorders

Machine learning research based on diffusion tensor images to distinguish between anorexia nervosa and bulimia nervosa.

BACKGROUND: Anorexia nervosa (AN) and bulimia nervosa (BN), two subtypes of eating disorders, often present diagnostic challenges due to their overlapping symptoms. Machine learning has proven its capacity to improve group classification without requiring researchers to specify variables. The study aimed to distinguish between AN and BN using machine learning models based on diffusion tensor image...

Comparing clinical decision-making of AI technology to a multi-professional care team in an electronic cognitive behavioural therapy program for depression: protocol.

INTRODUCTION: Depression is a leading cause of disability worldwide, affecting up to 300 million people globally. Despite its high prevalence and debilitating effects, only one-third of patients newly diagnosed with depression initiate treatment. Electronic cognitive behavioural therapy (e-CBT) is an effective treatment for depression and is a feasible solution to make mental health care more acce...

Deep learning for the prediction of clinical outcomes in internet-delivered CBT for depression and anxiety.

In treating depression and anxiety, just over half of all clients respond. Monitoring and obtaining early client feedback can allow for rapidly adapte...

Comparative and Predictive Analysis of Clinical and Metabolic Features of Anorexia Nervosa and Bulimia Nervosa.

BACKGROUND: Eating disorders have become increasingly prevalent over the years; the age at which they appear has decreased, and they can lead to serio...

Robot-assisted total remnant gastrectomy for interposed jejunal pouch dysfunction 25 years after proximal gastrectomy for gastric cancer: A case report.

Proximal gastrectomy (PG) in combination with jejunal pouch interposition is a technique aimed at improving the postoperative dietary outcomes; howeve...

Predicting the evolution trajectory of population-driven connectional brain templates using recurrent multigraph neural networks.

The mapping of the time-dependent evolution of the human brain connectivity using longitudinal and multimodal neuroimaging datasets provides insights ...

Enhancing the quality of cognitive behavioral therapy in community mental health through artificial intelligence generated fidelity feedback (Project AFFECT): a study protocol.

BACKGROUND: Each year, millions of Americans receive evidence-based psychotherapies (EBPs) like cognitive behavioral therapy (CBT) for the treatment o...

Predictors of accurate intrapedicular screw placement in single-level lumbar (L4-5) fusion: robot-assisted pedicle screw, traditional pedicle screw, and cortical bone trajectory screw insertion.

BACKGROUND: The superiorities in proximal facet joint protection of robot-assisted (RA) pedicle screw placement and screw implantation via the cortica...

Liver Damage Is Related to the Degree of Being Underweight in Anorexia Nervosa and Improves Rapidly with Weight Gain.

Background: The present study investigates the relationship between hypertransaminasemia and malnutrition on the basis of a very large number of patie...

Machine learning for genetic prediction of psychiatric disorders: a systematic review.

Machine learning methods have been employed to make predictions in psychiatry from genotypes, with the potential to bring improved prediction of outco...

Computer-aided therapeutic diagnosis for anorexia.

BACKGROUND: Anorexia nervosa is a clinical disorder syndrome of the wide spectrum without a fully recognized etiology. The necessary issue in the clin...

Predicting cognitive behavioral therapy outcome in the outpatient sector based on clinical routine data: A machine learning approach.

The availability of large-scale datasets and sophisticated machine learning tools enables developing models that predict treatment outcomes for indivi...

Towards integrating personalized feedback research into clinical practice: Development of the Trier Treatment Navigator (TTN).

In this study, a computer-based feedback, decision and clinical problem-solving system for clinical practice will be described - the Trier Treatment N...

Application of machine learning to structural connectome to predict symptom reduction in depressed adolescents with cognitive behavioral therapy (CBT).

PURPOSE: Adolescent major depressive disorder (MDD) is a highly prevalent, incapacitating and costly illness. Many depressed teens do not improve with...

Quantification of the constituents of the traditional Korea medicine, Samryeongbaekchul-san, and assessment of its antiadipogenic effect.

Samryeongbaekchul-san (SBS) is a traditional herbal formula, which is used for the treatment of dyspepsia, chronic gastritis, and anorexia in Korea. T...

An outbreak of classical swine fever in pigs in Bangladesh, 2015.

In a group of 22 healthy pigs aged between 4 and 6 months, 2 pigs became ill with high fever, complete anorexia, cough and abnormal swaying movements ...

Ontology-based systematical representation and drug class effect analysis of package insert-reported adverse events associated with cardiovascular drugs used in China.

With increased usage of cardiovascular drugs (CVDs) for treating cardiovascular diseases, it is important to analyze CVD-associated adverse events (AE...

Anesthetic approaches in carotid body tumor surgery.

OBJECTIVE: Carotid body tumors (CBT) are benign tumors that originate from neural non-chromaffin cells that are typically localized near carotid bifur...

Development of two artificial neural network models to support the diagnosis of pulmonary tuberculosis in hospitalized patients in Rio de Janeiro, Brazil.

Pulmonary tuberculosis (PTB) remains a worldwide public health problem. Diagnostic algorithms to identify the best combination of diagnostic tests for...

Machine learning derived risk prediction of anorexia nervosa.

BACKGROUND: Anorexia nervosa (AN) is a complex psychiatric disease with a moderate to strong genetic contribution. In addition to conventional genome ...