AI Model Improves Delirium Prediction, Leading to Better Health Outcomes for Hospitalized Patients
An artificial intelligence (AI) model improved outcomes in hospitalized patients by quadrupling the rate of detection and treatment of delirium. The model identifies patients at high risk for delirium and alerts a specially-trained team to assess the patient and create a treatment plan, if needed.
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AI-Human Task-Sharing could Cut Mammography Screening Costs by Up to 30%
The most effective way to harness the power of artificial intelligence (AI) when screening for breast cancer may be through collaboration with human radiologists - not by wholesale replacing them, says new research co-written by a University of Illinois Urbana-Champaign expert in the intersection of health care and technology.
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AI-Powered Precision: Unlocking the Future of Immunotherapy through Immunogenomics, Radiomics, and Pathomics
A team of researchers from the Department of Diagnostic and Therapeutic Ultrasonography at the Tianjin Medical University Cancer Institute & Hospital, have published a review in Cancer Biology & Medicine. The paper underscores the potential of AI to decode complex biological data with unprecedented speed and accuracy.
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SALSA: A New AI Tool for the Automated and Precise Analysis of Liver Tumors
Investigators of the Vall d'Hebron Institute of Oncology's (VHIO) Radiomics Group, led by Raquel Perez-Lopez, have developed SALSA (System for Automatic Liver tumor Segmentation And detection), a fully automated deep learning-driven tool for the precise and completely automated detection and monitoring of liver tumors (hepatocellular carcinoma).
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AI could Help Improve Early Detection of Interval Breast Cancers
A new study led by investigators at the UCLA Health Jonsson Comprehensive Cancer Center suggests that artificial intelligence (AI) could help detect interval breast cancers - those that develop between routine screenings - before they become more advanced and harder to treat.
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Building Trust in Artificial Intelligence for Healthcare: Lessons from Clinical Oncology
A new review, published in the peer-reviewed journal AI in Precision Oncology, explores the multifaceted reasons behind the skepticism surrounding artificial intelligence (AI) technologies in healthcare and advocates for approaches to build confidence in AI applications.
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AI Tool Helps Predict Relapse of Pediatric Brain Cancer
Artificial intelligence (AI) shows tremendous promise for analyzing vast medical imaging datasets and identifying patterns that may be missed by human observers. AI-assisted interpretation of brain scans may help improve care for children with brain tumors called gliomas, which are typically treatable but vary in risk of recurrence.
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