The Diagnostic Imaging AI (artificial intelligence) focus page provides information, videos, podcasts, and the latest news about product developments, trial results, screening guidelines, and protocol guidance that touch on the development and use of AI across the healthcare continuum.
May 8th 2024
In a study involving over 1,000 visible prostate lesions on biparametric MRI, a deep learning algorithm detected 96 percent of clinically significant prostate cancer (csPCa) in comparison to a 98 percent detection rate for an expert genitourinary radiologist.
Medical Crossfire®: How Can Thoracic Teams Facilitate Optimized Care of Patients With Stage I-III EGFR Mutation-Positive NSCLC?
May 21, 2024
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Medical Crossfire®: Critical Questions on Diagnosis, Sequencing, and Selection of Systemic and Radioligand Therapy Options for Patients with GEP-NETs
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Medical Crossfire®: Expert Exchanges to Maximize Clinical Outcomes for Patients with CRPC Through Evidence-Based Personalized Therapy
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23rd Annual International Congress on the Future of Breast Cancer® West
July 12-13, 2024
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25th Annual International Lung Cancer Congress®
July 25-27, 2024
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2023 ASCO Direct™ Highlights: Practice-Changing Data From the Leading Oncology Conference
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6th Annual Precision Medicine Symposium: An Illustrated Tumor Board
October 18-19, 2024
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Community Practice Connections™: 24th Annual International Lung Cancer Congress®
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19th Annual New York Lung Cancers Symposium®
November 16, 2024
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Medical Crossfire®: How Does Recent Evidence on PARP Inhibitors and Combinations Inform Treatment Planning for Prostate Cancer Now and In the Future?
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Medical Crossfire®: How Do the Experts Select and Sequence Therapies to Optimize Patient Outcomes and Quality of Life in Advanced Prostate Cancer?
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Lung Cancer Tumor Board®: Enhancing Multidisciplinary Communication to Optimize Immunotherapy in Stage I-III NSCLC
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Clinical Vignettes™: The Experts Explain How They Integrate PET Imaging into Metastatic HR+ Breast Cancer Care Settings
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School of Breast Oncology® Live Video Webcast: Clinical Updates from San Antonio
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Community Practice Connections™: The 2nd Annual Hawaii Lung Cancers Conference®
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Large Mammography Study Shows Significant Benefits with AI-Aided Screening
August 1st 2023Reportedly the first randomized trial to examine the impact of artificial intelligence (AI) on screening mammography, researchers found AI-aided screening led to a 20 percent increase in breast cancer detection and a 44.3 percent decrease in mammography screening workload.
Researchers Note Lack of Benefit with AI in Women with Dense Breasts
July 28th 2023In a study of over 1.300 women with dense breasts, the combination of mammography and ultrasound had a recall rate of 11.7 percent, a specificity rate of 89.1 percent and an accuracy rate of 89.2 percent in comparison to a 21.4 percent recall rate, 79.4 percent specificity and 79.5 percent accuracy for the combination of mammography, ultrasound, and artificial intelligence (AI).
Mammography-Based Deep Learning Model May Help Detect Precancerous Changes in High-Risk Women
July 27th 2023In a dataset enriched for African American women, BRCA mutation carriers and those with benign breast disease, a mammography-based deep learning model demonstrated a five-year AUC of 63 percent for predicting breast cancer in comparison to 54 percent for BI-RADS assessment.
Study: AI Assessment of Chest CT May Predict Multiple Mortality Risks
July 26th 2023In a study of over 20,700 people, researchers found that artificial intelligence (AI) analysis of body composition measurements via lung cancer screening computed tomography (CT) exams improves the prediction of mortality risks for lung cancer, cardiovascular disease, and all-cause mortality.
Can AI Bolster MRI Lesion Detection and Segmentation in Patients with Multiple Sclerosis?
July 19th 2023An artificial intelligence model, trained on MRI and FLAIR imaging from over 900 patients with multiple sclerosis, demonstrated a 96 percent accuracy rate and 99 percent specificity rate for contrast-enhancing lesions in this patient population.
Ultromics Gets HCPCS Code for AI-Powered EchoGo Heart Failure Device
July 6th 2023An artificial intelligence (AI)-enabled platform that can reportedly diagnose heart failure with preserved ejection fraction (HFpEF) through analysis of a single echocardiogram view, the EchoGo Heart Failure now has a HCPCS code for use of the technology in outpatient settings for Medicare beneficiaries.
Icometrix Gets First CPT III Code Issued by AMA for AI Brain MRI Software
July 3rd 2023Reportedly receiving the first Current Procedural Terminology (CPT) III code from the American Medical Association (AMA) for artificial intelligence (AI)-enabled brain magnetic resonance imaging (MRI) software, Icometrix says its adjunctive quantification software can be utilized for diagnosis and assessment of conditions ranging from Alzheimer’s disease and epilepsy to stroke and dementia.
Deep Learning Detection of Mammography Abnormalities: What a New Study Reveals
June 19th 2023In multiple mammography datasets with the original radiologist-detected abnormality removed, deep learning detection of breast cancer had an average area under the curve (AUC) of 87 percent and an accuracy rate of 83 percent, according to research presented at the recent Society for Imaging Informatics in Medicine (SIIM) conference.
Study Assesses Ability of Mammography AI Algorithms to Predict Breast Cancer Risk
June 7th 2023Five artificial intelligence (AI) algorithms for mammography assessment were better at predicting breast cancer risk over five years than the Breast Cancer Surveillance Consortium (BCSC) risk model, according to new retrospective research involving over 13,000 women.
Multicenter Breast Ultrasound Study: AI Bolsters Accuracy and Specificity of BI-RADS Classifications
May 24th 2023Emerging breast ultrasound research showed the use of computer-aided diagnosis (CAD), powered by deep learning, led to 24 percent and 36.9 percent improvements in accuracy and specificity, respectively, in the use of BI-RADS classifications by radiologists without breast ultrasound expertise.
Digital Mammography Meta-Analysis Suggests AI Performs as Well as Radiologists
May 24th 2023Six reader studies on digital mammography revealed a pooled sensitivity rate of 80.8 percent for stand-alone artificial intelligence (AI) in comparison to 72.4 percent for radiologist assessment while seven historic cohort studies showed a 75.8 percent pooled sensitivity rate for stand-alone AI versus 72.6 percent for radiologist interpretation of digital mammography.