AIMC Topic: Neoplasms

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Leveraging Artificial Intelligence to Uncover Symptom Burden in Palliative Care: Analysis of Nonscheduled Visits Using a Phi-3 Small Language Model.

JCO global oncology
PURPOSE: This study aimed to differentiate nonscheduled visits (NSVs) in an outpatient palliative care setting that are driven by or accompanied by uncontrolled symptoms from those that are administrative or routine, such as prescription refills and ...

Identification of Crohn's Disease-Related Biomarkers and Pan-Cancer Analysis Based on Machine Learning.

Mediators of inflammation
: In recent years, the incidence of Crohn's disease (CD) has shown a significant global increase, with numerous studies demonstrating its correlation with various cancers. This study aims to identify novel biomarkers for diagnosing CD and explore the...

Mitigating ambient RNA and doublets effects on single cell transcriptomics analysis in cancer research.

Cancer letters
In cancer biology, where understanding the tumor microenvironment at high resolution is vital, ambient RNA contamination becomes a considerable problem. This hinders accurate delineation of intratumoral heterogeneity, complicates the identification o...

Effect of a ChatGPT-based digital counseling intervention on anxiety and depression in patients with cancer: A prospective, randomized trial.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Psychological distress is prevalent among newly diagnosed cancer patients, often exacerbating treatment-related anxiety and depression. Artificial intelligence (AI)-driven interventions, such as large language models (LLMs), offer scalabl...

Public Awareness of and Attitudes Toward the Use of AI in Pathology Research and Practice: Mixed Methods Study.

Journal of medical Internet research
BACKGROUND: The last decade has witnessed major advances in the development of artificial intelligence (AI) technologies for use in health care. One of the most promising areas of research that has potential clinical utility is the use of AI in patho...

M4: Multi-proxy multi-gate mixture of experts network for multiple instance learning in histopathology image analysis.

Medical image analysis
Multiple instance learning (MIL) has been successfully applied for whole slide images (WSIs) analysis in computational pathology, enabling a wide range of prediction tasks from tumor subtyping to inferring genetic mutations and multi-omics biomarkers...

Clinical Trial Notifications Triggered by Artificial Intelligence-Detected Cancer Progression: A Randomized Trial.

JAMA network open
IMPORTANCE: Historically, fewer than 10% of adults with cancer have enrolled in clinical trials. Computational tools have been developed to match patients to trials, but these tools are relevant only when patients need new treatment.

Artificial Intelligence Performance in Image-Based Cancer Identification: Umbrella Review of Systematic Reviews.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) has the potential to transform cancer diagnosis, ultimately leading to better patient outcomes.

Toward a human-centric co-design methodology for AI detection of differences between planned and delivered dose in radiotherapy.

Journal of applied clinical medical physics
INTRODUCTION: Many artificial intelligence (AI) solutions have been proposed to enhance the radiotherapy (RT) workflow, but limited applications have been implemented to date, suggesting an implementation gap. One contributing factor to this gap is a...

Anticancer drug response prediction integrating multi-omics pathway-based difference features and multiple deep learning techniques.

PLoS computational biology
Individualized prediction of cancer drug sensitivity is of vital importance in precision medicine. While numerous predictive methodologies for cancer drug response have been proposed, the precise prediction of an individual patient's response to drug...