AIMC Topic: Female

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Research on driving factors of consumer purchase intention of artificial intelligence creative products based on user behavior.

Scientific reports
With the continuous advancement of artificial intelligence (AI) technology, AIGC (AI-generated content) has increasingly permeated various sectors, leading to a significant transformation in the design industry. This study aims to explore user purcha...

Feasibility of machine learning-based modeling and prediction to assess osteosarcoma outcomes.

Scientific reports
Osteosarcoma, an aggressive bone malignancy predominantly affecting children and adolescents, is characterized by a poor prognosis and high mortality rates. The development of reliable prognostic tools is critical for advancing personalized treatment...

Personalized prediction of negative affect in individuals with serious mental illness followed using long-term multimodal mobile phenotyping.

Translational psychiatry
Heightened negative affect is a core feature of serious mental illness. Over 90% of American adults own a smartphone, equipped with an array of sensors which can continuously and unobtrusively measure behaviors (e.g., activity levels, location, and p...

A CNN-based approach for detecting eye blink episodes in EEG signals.

Journal of neural engineering
This study aims to develop and evaluate a convolutional neural network (CNN)-based architecture for detecting eye blink episodes in electroencephalographic (EEG) signals, with a focus on the precise detection of individual events rather than their cl...

Patient research priorities in melanoma: a national qualitative interview study.

The British journal of dermatology
BACKGROUND: Outcomes for advanced melanoma have improved following the advent of immunotherapy and targeted therapy. This heralds a need for reconsideration of future research agendas. Patients can - and are keen to - help identify and prioritize res...

Lexical associations can characterize clinical documentation trends related to palliative care and metastatic cancer.

Scientific reports
Palliative care is known to improve quality of life in advanced cancer. Natural language processing offers insights to how documentation around palliative care in relation to metastatic cancer has changed. We analyzed inpatient clinical notes using u...

Characterizing low femoral neck BMD in Qatar Biobank participants using machine learning models.

BMC musculoskeletal disorders
BACKGROUND: Identifying determinants of low bone mineral density (BMD) is crucial for understanding the underlying pathobiology and developing effective prevention and management strategies. Here we applied machine learning (ML) algorithms to predict...

Machine learning and single-cell analysis uncover distinctive characteristics of CD300LG within the TNBC immune microenvironment: experimental validation.

Clinical and experimental medicine
Investigating the essential function of CD300LG within the tumor microenvironment in triple-negative breast cancer (TNBC). Transcriptomic and single-cell data from TNBC were systematically collected and integrated. Four machine learning algorithms we...

An integrated deep learning model for early and multi-class diagnosis of Alzheimer's disease from MRI scans.

Scientific reports
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that severely affects memory, behavior, and cognitive function. Early and accurate diagnosis is crucial for effective intervention, yet detecting subtle changes in the early stages ...

A self-supervised multimodal deep learning approach to differentiate post-radiotherapy progression from pseudoprogression in glioblastoma.

Scientific reports
Accurate differentiation of pseudoprogression (PsP) from True Progression (TP) following radiotherapy (RT) in glioblastoma patients is crucial for optimal treatment planning. However, this task remains challenging due to the overlapping imaging chara...