Schizophrenia

Increasing value in the Veterans Affairs Healthcare System (VA) with precision health: a continuing landmark collaboration with the Department of Energy.

OBJECTIVE: Phase II of MVP-CHAMPION, a federal collaboration between the Veterans Affairs Healthcare...

Using large language models to identify geriatric assessment domains in patients with advanced cancer: A feasibility study.

INTRODUCTION: In older adults with cancer, geriatric assessment (GA) can improve care quality. In-pe...

A frontotemporal dementia-like phenotype in schizophrenia: links to striatal dopamine and iron accumulation.

Some schizophrenia patients share characteristics with behavioral variant frontotemporal dementia (b...

Causal ordinal connections based characterization of weighted effective brain network for schizophrenia detection.

The human brain is responsible for a wide range of a person's behavioral and cognitive capabilities....

EEG-based schizophrenia detection using handcrafted biomarkers and a TOA-optimized hybrid multi-branch CNN-Transformer framework.

Schizophrenia is a chronic psychiatric disorder for which electroencephalography (EEG) offers a low-...

A Bibliometric Examination of EEGLAB Publications in Scopus and WoS Indexed Sources: A 20-Year Study of Asia-Pacific and Arabian Countries.

IntroductionEEGLAB is a widely used software for analyzing electroencephalography (EEG) datasets, wi...

Omission and hallucination prevalence of clinical guidelines in diagnostic large language model outputs.

OBJECTIVE: Meaningful assessments of how large language models (LLMs) incorporate clinical guideline...

Exploring schizophrenia-associated image-derived digital phenotypes in dual-energy X-ray densitometer scans of non-dominant distal forearm: An explainable machine-learning framework.

Schizophrenia remains diagnosed primarily through clinical assessment, which motivates the researche...

Neuroimaging-Based Subgroups in Schizophrenia: A Critical Appraisal of Clustering Studies.

Efforts to define biologically grounded subtypes of schizophrenia have increasingly leveraged neuroi...

Factors influencing disinformation avoidance behavior among generative artificial intelligence users: A cognition-affect-conation framework.

This study aimed to uncover the mechanisms driving disinformation avoidance behavior among generativ...

Using Large Language Models to Identify Patient-Oncologist Communication Domains: A Feasibility Study.

BACKGROUND: The American Society of Clinical Oncology (ASCO) convened a multidisciplinary panel in 2...

Physical mechanisms governing generalization and hallucination in deep learning for imaging through scattering media.

Deep learning has revolutionized computational imaging, yet its real-world deployment remains constr...

A multimodal fNIRS-based machine learning model for symptom assessment and treatment response prediction in schizophrenia.

OBJECTIVE: Predicting early symptom severity and treatment response in schizophrenia is crucial for ...

A comparative evaluation of EEG-based deep learning models for schizophrenia detection with cross-dataset validation and explainable AI.

OBJECTIVES: Schizophrenia is a neuropsychiatric disorder that affects emotional, behavioral, and bra...

Performance evaluation of five large language models for assisting in the interpretation of urinalysis reports for kidney diseases: a real-world study.

OBJECTIVES: Large language models (LLMs) show promise for interpreting laboratory reports, yet real-...

Non-European migrants with schizophrenia spectrum disorders in Swiss forensic and general psychiatric care facilities - A comparative study using machine learning.

Personal history of migration poses an important risk factor for schizophrenia spectrum disorders (S...

Scenario-based evaluation of large language models for reference accuracy in dermatology: literature retrieval on latent tuberculosis in psoriasis patients on anti-IL-17/23 therapy.

BACKGROUND: Large language models (LLMs) could accelerate clinical literature searches, but their re...

Are routinely collected clinical and sociodemographic characteristics associated with social functioning and activities of daily living in schizophrenia? A machine learning approach descriptive of a schizophrenia cohort.

Patients with schizophrenia often experience substantial impairments in social functioning and activ...

Extrapyramidal symptom severity across machine learning-derived neuroanatomical subtypes of schizophrenia.

Development and validation of a precision treatment rules for first-line antipsychotic recommendations in first episode psychosis jointly incorporating effectiveness, side effects and patient preferences.

Selecting first-line antipsychotic medication for first episode of psychosis patients is a very chal...

Views of People With Psychosis About Algorithm-Based Relapse Prediction and Data Sharing: Qualitative Study.

BACKGROUND: Preventing relapses of psychosis is difficult and important. Digital remote monitoring (...