Results 71 to 80 of about 57,139 (318)
Perspectives on the Current and Future State of Artificial Intelligence in Medical Genetics
ABSTRACT Artificial intelligence (AI) is rapidly transforming numerous aspects of daily life, including clinical practice and biomedical research. In light of this rapid transformation, and in the context of medical genetics, we assembled a group of leaders in the field to respond to the question about how AI is affecting, and especially how AI will ...
Benjamin D. Solomon+20 more
wiley +1 more source
Visual hallucinations in neurological and ophthalmological disease: pathophysiology and management
Visual hallucinations are common in older people and are especially associated with ophthalmological and neurological disorders, including dementia and Parkinson’s disease.
J. O'Brien+26 more
semanticscholar +1 more source
Using Telemedicine to Assess and Manage Psychosis Among Outpatients with Neurodegenerative Disease
Craig Chepke,1– 3 Lynn W Shaughnessy,4 Stephen Brunton,5,6 Jill G Farmer,7,8 Andrew S Rosenzweig,9 George T Grossberg,10 Wendy L Wright11 1Excel Psychiatric Associates, Huntersville, NC, USA; 2Atrium Health, Charlotte, NC, USA; 3University of North ...
Chepke C+6 more
doaj
Recognizing Psychosis in Autism Spectrum Disorder
There is strong evidence for the existence of a high comorbidity between autism and psychosis with percentages reaching up to 34. 8% and several significant implications for treatment and prognosis of these patients.
Michele Ribolsi+15 more
doaj +1 more source
ABSTRACT Schizophrenia is a neurodevelopmental psychiatric disorder characterized by symptoms of psychosis, thought disorder, and flattened affect. Immune mechanisms are associated with schizophrenia, though the precise nature of this relationship (causal, correlated, consequential) and the mechanisms involved are not fully understood.
David Stacey+6 more
wiley +1 more source
HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models [PDF]
Large language models (LLMs), such as ChatGPT, are prone to generate hallucinations, i.e., content that conflicts with the source or cannot be verified by the factual knowledge. To understand what types of content and to which extent LLMs are apt to hallucinate, we introduce the Hallucination Evaluation benchmark for Large Language Models (HaluEval), a
arxiv
The Hallucinations of Widowhood [PDF]
227 widows and 66 widowers were interviewed to determine the extent to which they had hallucinatory experiences of their dead spouse. The people interviewed formed 80.7% of all widowed people resident within a defined area, in mid-Wales, and 94.2% of those suitable, through the absence of incapacitating illness, for interview.Almost half the people ...
openaire +2 more sources
Abstract US clinical practice guidelines for the diagnostic evaluation of cognitive impairment due to Alzheimer's disease (AD) or AD and related dementias (ADRD) are decades old and aimed at specialists. This evidence‐based guideline was developed to empower all—including primary care—clinicians to implement a structured approach for evaluating a ...
Alireza Atri+10 more
wiley +1 more source
Evaluation and Analysis of Hallucination in Large Vision-Language Models [PDF]
Large Vision-Language Models (LVLMs) have recently achieved remarkable success. However, LVLMs are still plagued by the hallucination problem, which limits the practicality in many scenarios. Hallucination refers to the information of LVLMs' responses that does not exist in the visual input, which poses potential risks of substantial consequences ...
arxiv
Objective Following 2 decades of research on cognitive behavioral therapy for psychosis (CBTp), it is relevant to consider at which point the evidence base is considered sufficient.
David T Turner+4 more
semanticscholar +1 more source