AIMC Topic: Family

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Using short-range and long-range functional connectivity to identify schizophrenia with a family-based case-control design.

Psychiatry research. Neuroimaging
Abnormal short-range and long-range functional connectivities (FCs) have been implicated in the neurophysiology of schizophrenia. This study was conducted to examine the potential of short-range and long-range FCs for differentiating the patients fro...

Towards person-centered neuroimaging markers for resilience and vulnerability in Bipolar Disorder.

NeuroImage
Improved clinical care for Bipolar Disorder (BD) relies on the identification of diagnostic markers that can reliably detect disease-related signals in clinically heterogeneous populations. At the very least, diagnostic markers should be able to diff...

Needs of bereaved families of patients with cancer towards artificial intelligence in palliative care: A web-based survey.

European journal of oncology nursing : the official journal of European Oncology Nursing Society
PURPOSE: Artificial intelligence (AI) systems in palliative care have garnered attention and popularity in recent years. Understanding patient and family needs is crucial for developing and implementing AI systems in palliative care. Few studies in p...

Using a Robot to Address the Well-Being, Social Isolation, and Loneliness of Care Home Residents via Video Calls: Qualitative Feasibility Study.

JMIR formative research
BACKGROUND: About 40,000 people are living in Norwegian care homes, where a majority are living with a dementia diagnosis. Social isolation and loneliness are common issues affecting care home residents' quality of life. Due to visitation restriction...

Acceptance of Telepresence Robotics, Telecare and Teletherapy Among Stroke Patients, Relatives and Therapy Staff.

Studies in health technology and informatics
BACKGROUND: Stroke as a cause of disability in adulthood causes an increasing demand for therapy and care services, including telecare and teletherapy.

[Application of convolutional neural networks for the classification of metaphase chromosomes].

Zhonghua yi xue yi chuan xue za zhi = Zhonghua yixue yichuanxue zazhi = Chinese journal of medical genetics
OBJECTIVE: To train a deep convolutional neural networks (CNN) using a labeled data set to classify the metaphase chromosomes and test its accuracy for chromosomal identification.

Analyzing Dementia Caregivers' Experiences on Twitter: A Term-Weighted Topic Modeling Approach.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Dementia profoundly impacts patients and their families, making it essential to understand the experiences and concerns offamily caregivers for enhanced support and care. This study introduces a novel approach to analyzing tweets from individuals who...

Ontology-Based Natural Language Processing of Social Media Data in the Assessment of Health Information Sought During Pregnancy.

Studies in health technology and informatics
This study analyzed collected social media data from South Korea containing keywords related to "pregnancy" using ontology-based natural language processing. Of the 504,725 documents, those containing concepts related to "maternal emotion" were the m...

Natural language processing to measure the frequency and mode of communication between healthcare professionals and family members of critically ill patients.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To apply natural language processing (NLP) techniques to identify individual events and modes of communication between healthcare professionals and families of critically ill patients from electronic medical records (EMR).

Spoken words as biomarkers: using machine learning to gain insight into communication as a predictor of anxiety.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The goal of this study was to explore whether features of recorded and transcribed audio communication data extracted by machine learning algorithms can be used to train a classifier for anxiety.