AIMC Topic: Humans

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A deep learning approach for virtual contrast enhancement in Contrast Enhanced Spectral Mammography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Contrast Enhanced Spectral Mammography (CESM) is a dual-energy mammographic imaging technique that first requires intravenously administering an iodinated contrast medium. Then, it collects both a low-energy image, comparable to standard mammography,...

Meta-Analysis of the Efficacy of Raman Spectroscopy and Machine-Learning-Based Identification of Glioma Tissue.

World neurosurgery
Intraoperative Raman spectroscopy (RS) has been identified as a potential tool for surgeons to rapidly and noninvasively differentiate between diseased and normal tissue. Since the previous meta-analysis on the subject was published in 2016, improvem...

Consolidated Health Economic Evaluation Reporting Standards for Interventions That Use Artificial Intelligence (CHEERS-AI).

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: Economic evaluations (EEs) are commonly used by decision makers to understand the value of health interventions. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS 2022) provide reporting guidelines for EEs. Healthcar...

Temporal prediction of suicidal ideation in an ecological momentary assessment study with recurrent neural networks.

Journal of affective disorders
INTRODUCTION: Ecological Momentary Assessment (EMA) holds promise for providing insights into daily life experiences when studying mental health phenomena. However, commonly used mixed-effects linear statistical models do not fully utilize the richne...

Artificial Intelligence and Lung Pathology.

Advances in anatomic pathology
This manuscript provides a comprehensive overview of the application of artificial intelligence (AI) in lung pathology, particularly in the diagnosis of lung cancer. It discusses various AI models designed to support pathologists and clinicians. AI m...

Novel drug discovery: Advancing Alzheimer's therapy through machine learning and network pharmacology.

European journal of pharmacology
Alzheimer's disease (AD), marked by tau tangles and amyloid-beta plaques, leads to cognitive decline. Despite extensive research, its complex etiology remains elusive, necessitating new treatments. This study utilized machine learning (ML) to analyze...

Neural topic models with survival supervision: Jointly predicting time-to-event outcomes and learning how clinical features relate.

Artificial intelligence in medicine
We present a neural network framework for learning a survival model to predict a time-to-event outcome while simultaneously learning a topic model that reveals feature relationships. In particular, we model each subject as a distribution over "topics...

Evaluation of responses to cardiac imaging questions by the artificial intelligence large language model ChatGPT.

Clinical imaging
PURPOSE: To assess ChatGPT's ability as a resource for educating patients on various aspects of cardiac imaging, including diagnosis, imaging modalities, indications, interpretation of radiology reports, and management.

Masked hypergraph learning for weakly supervised histopathology whole slide image classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Graph neural network (GNN) has been extensively used in histopathology whole slide image (WSI) analysis due to the efficiency and flexibility in modelling relationships among entities. However, most existing GNN-based WSI a...

Knowledge enhanced attention aggregation network for medicine recommendation.

Computational biology and chemistry
The combination of deep learning and the medical field has recently achieved great success, particularly in recommending medicine for patients. However, patients' clinical records often contain repeated medical information that can significantly impa...