Joseph A. Sparano, MD, on Multimodal AI Models for Predicting Breast Cancer Recurrence
Joseph A. Sparano, MD, of the Icahn School of Medicine at Mount Sinai, discusses the performance of experimental multimodal artificial intelligence (AI) models integrating clinical, molecular, and histopathologic features to provide prognostic information for early and late recurrence using primary tumor samples and clinical data from participants in the TAILORx trial (Abstract GS1-08).
AI Tool May Predict Cardiac Events in Patients With Cancer and Acute Coronary Syndrome
An artificial intelligence (AI)-based risk prediction model, ONCO-ACS, showed possible favorable clinical utility as a practical tool for predicting cardiovascular death, myocardial infarction, and ischemic stroke events in patients with cancer and acute coronary syndrome, according to findings...
Deep-Learning CT Biomarker Predicts Survival Better Than Traditional Measures in Immunotherapy-Treated Advanced NSCLC
Sako et al conducted a prognostic study to evaluate whether a fully automated deep-learning radiomic biomarker based on serial CT scans could improve prediction of overall survival in patients with advanced non–small cell lung cancer (NSCLC) receiving immune checkpoint inhibitors. Their findings,...
Randomized Trial Shows AI-Supported Mammography Improves Sensitivity and Lowers Interval Cancer Rate
A randomized, controlled clinical trial for artificial intelligence (AI)–supported mammography readings, called the MASAI trial, demonstrated that AI reads of mammogram scans led to fewer interval breast cancer diagnoses than with standard double reads by radiologists, according to findings...
Machine Learning–Enhanced Prognostic Scoring Predicts Survival and Classifies Risk From Spinal Metastases
A prognostic scoring system for predicting 1-year survival in patients with advanced cancer and spinal metastases was enhanced with machine learning for greater accuracy, according to the results of a Japanese multicenter study published in Spine. "This model provides a practical risk assessment...
CRI Launches Open Database for Immunotherapy Cancer Research
The Cancer Research Institute (CRI) in collaboration with 10x Genomics, Stanford University School of Medicine, the University of Pennsylvania Perelman School of Medicine, and Memorial Sloan Kettering Cancer Center, has launched an open foundational database for cancer immunotherapy research. The...
Most Patients Support Use of AI in Mammogram Readings, Survey Reveals
The results of a recent survey showed that patients largely support the use of artificial intelligence (AI) to aid radiologists in reading mammograms. The findings, which were published in Breast Cancer Research and Treatment, also indicated acceptance varied in association with factors such as...
Regulatory Agencies Establish Principles of Good AI Use in Drug Development
The U.S. Food and Drug Administration's (FDA) Center for Drug Evaluation and Research (CDER) and Center for Biologics Evaluation and Research (CBER) have collaborated with the European Medicines Agency (EMA) to develop a set of 10 guiding principles for good uses of artificial intelligence (AI) in...
HCC: LLM Advice and Treatment Concordance
Commonly used large language models (LLMs) were able to provide appropriate, guideline-aligned treatment recommendations for patients with straightforward cases of early-stage hepatocellular carcinoma; however, greater disagreement with physician recommendations was seen in cases of late-stage...
Global Cancer Survival Gaps Assessed Using a Country-Level Machine-Learning Framework
A machine-learning model has calculated country-specific cancer mortality-to-incidence ratios and evaluated the factors that contribute the most to each country's survival gaps. Additionally, the artificial intelligence (AI) tool mapped out actions each country could take to improve cancer...
Machine Learning–Guided ‘Optical Biopsy’ Accurately Identifies Malignant Lung Nodules Intraoperatively
In a cohort study reported in JAMA Network Open, Azari et al evaluated whether machine learning–guided analysis of intraoperative molecular imaging (IMI) data could accurately and rapidly determine the malignant potential of indeterminate lung nodules during surgery. The study was undertaken to...
Machine Learning Approach Accelerates Discovery of Novel CDK9 Inhibitors
A virtual screening campaign using machine learning identified molecules with potential for development as novel CDK9 inhibitors for the treatment of cancer, according to early research findings published in Biomolecules. Integration of artificial intelligence (AI) into the drug discovery phase...
Breast Cancer Recurrence Risk Determined by Deep Learning Model Trained on Histopathologic Slides
A deep learning model demonstrated the ability to predict breast cancer recurrence risk and possible benefit from the addition of chemotherapy based on histopathologic images rather than genomic testing in patients with hormone receptor–positive, HER2-negative breast cancer, according to findings...
Using AI to Ensure That All Patients With Cancer Have Access to Precision Oncology Care
Steve Brown, Founder and Chief Executive Officer of CureWise (curewise.com), an artificial intelligence (AI)-driven patient advocacy app, describes his year-long quest to understand a series of symptoms that ultimately led to a diagnosis of light chain (AL) amyloidosis—a disease closely related to ...
AI-Based Imaging Model Predicts Extranodal Extension Burden and Improves Risk Stratification in Oropharyngeal Cancer
Prediction of the number of lymph nodes with extranodal extension in patients with oropharyngeal carcinoma through a deep learning imaging platform for autosegmentation may help to guide pretreatment patient risk stratification and treatment decision-making, according to the results of a multisite, ...
Most People Trust AI Less Than Physicians, Survey Finds
Two national surveys examining trust and acceptance of medical artificial intelligence (AI) have found that while most people are reluctant to use AI tools to diagnose their health condition, they see potential in the technology’s ability to help diagnose cancer. The findings, published by Sobolev...
AI Models Advance Individualized Breast Cancer Recurrence Risk Assessments
Two presentations at the 2025 San Antonio Breast Cancer Symposium (SABCS) highlighted new artificial intelligence (AI) tools and systems for improving distant recurrence risk stratification among patients with early-stage breast cancer. The first tested multimodal AI models with imaging, clinical,...
Can Multimodal AI Models Predict Distant Recurrence Risk in Patients With Early Breast Cancer?
Multimodal artificial intelligence (AI) models using a combination of molecular, imaging, and clinical features improved the individual prognostic assessment of patients with early breast cancer's risk of distant recurrence, according to an analysis presented at the 2025 San Antonio Breast Cancer...
AI Tops Density in Predicting Breast Cancer Risk
An image-only artificial intelligence (AI) model for predicting the 5-year risk of breast cancer provided stronger and more precise risk stratification than breast density assessment, according to a news statement issued about a study presented at the annual meeting of the Radiological Society of...
ASCO and AI in Oncology: Rooted in Human-Centered Care
ASCO’s mission to conquer cancer through research, education, and promotion of the highest quality patient care requires curiosity, open-mindedness, and an evidence-based approach to emerging technologies. ASCO is committed to helping the oncology community understand, develop, apply, and monitor...
How AI Is Ushering in a New Era in Cancer Care
On October 30, 2025, Google Cloud held its second annual Cancer AI Symposium to explore how artificial intelligence (AI) is advancing cancer research, diagnosis, and treatment, in unparalleled ways. Held at Google’s St. John’s Terminal office in New York City, the event brought together leaders in...
Validation of Pathology-AI Integration Tool for Risk Stratification in Locally Advanced Colon Cancer Without Chemotherapy
The Combined Analysis of Pathology and Artificial Intelligence (AI; CAPAI) model effectively stratified patients with colon cancer into distinct prognostic groups, identifying nearly half as low-risk, with “favorable” cancer-specific survival outcomes in the absence of adjuvant chemotherapy,...
Aaron Gerds, MD, on Using an AI System to Identify Patients Eligible for a Polycythemia Vera Trial
Aaron Gerds, MD, of Cleveland Clinic, reviews results of an evaluation of Synapsis AI, a medically trained, large language model–based end-to-end system, focusing on its accuracy and efficiency in identifying eligible patients for an active phase III polycythemia vera clinical trial (Abstract 4340).
Pancreatic Cancer Detection: AI vs Radiologists
In a study (PANORAMA) reported in The Lancet Oncology, Alves et al found that an artificial intelligence (AI) program developed by the investigators was significantly better at detecting pancreatic ductal adenocarcinoma when applied to standard-of-care computed tomography (CT) scans than were...
Image-Only AI Model Outperforms Breast Density Assessment for 5-Year Breast Cancer Risk Stratification
An image-only artificial intelligence (AI) model demonstrated stronger and more precise risk stratification than breast density assessment for predicting 5-year risk for developing breast cancer, according to findings from a study presented at the 2025 Annual Meeting of the Radiological Society of...
External Validation Confirms Ability of AI Model to Stratify Recurrence Risk in Early-Stage Lung Cancer
A machine learning–based survival model, incorporating preoperative CT images and routinely available clinical data, outperformed standard clinical staging systems in predicting recurrence after surgery in patients with lung cancer, especially in stage I, and showed correlations with established...
AI Simplifies Patients' Comprehension of CT Reports—but Errors Are Possible
Simplified oncologic computed tomography (CT) reports using large language models (LLMs) enabled patients to better understand the results of their restaging CT scans and reduced overall reading burden, according to the results of a study published in Radiology. However, the study also revealed...
Large AI Breast Cancer Screening Trial Increases Detection Rate by 20%
Using an artificial intelligence (AI)–integrated workflow, DeepHealth, in computer-aided detection of breast cancer from digital breast tomosynthesis exams found 21.6% more cases than the usual standard of care, according to findings from the AI-Supported Safeguard Review Evaluation (ASSURE) study...
New Computational Tool Shows Strong Accuracy in Predicting Cancer Drug Targets
Using a computational tool, DeepTarget, physicians were able to predict both primary and secondary targets of small-molecule agents for cancer treatment, according to findings from a study published in npj Precision Oncology. The study authors suggest that this represents a potentially significant...
NCCN Guidelines to Be Integrated Into OpenEvidence's Medical AI Platform
The National Comprehensive Cancer Network (NCCN) has entered into a licensing agreement with OpenEvidence that would make the NCCN Clinical Practice Guidelines in Oncology accessible through OpenEvidence's AI–powered medical platform. “This collaboration will help clinicians access trusted...
Physician-Complementing Artificial Intelligence in Oncology
Use of artificial intelligence (AI) in oncology is advancing rapidly. AI was first used for reading radiology images and analyzing pathology slides. More recently, use of AI has expanded to analyzing large clinical data sets (big data). The next envisioned role for AI in oncology encompasses many ...
Experts Outline Roadmap for Clinical Implementation of AI in Pediatric CNS Tumor Management
A subcommittee of the RAPNO (Response Assessment in Pediatric Neuro-Oncology) consortium that is focused on artificial intelligence (AI-RAPNO) has released guidance on the responsible implementation of AI in pediatric neuro-oncology in the form of a two-part policy review published in The Lancet...
Deep Learning and Mammography for Identifying Interval Breast Cancers
A deep learning algorithm developed for processing digital screening mammograms, Mirai, was able to detect interval breast cancers and identify women who would benefit from more frequent screenings, according to the results of a UK retrospective study published in Radiology. “If we called back 20% ...
Cancer Data Scientist Joins Translational Research Institute at Cedars-Sinai
Eytan Ruppin, MD, PhD, has been appointed Deputy Director of the Translational Research Institute as well as Director of Integrative Data Sciences in the Division of Surgical Research at Cedars-Sinai Cancer. “We are delighted to welcome Dr. Ruppin to Cedars-Sinai as a prestigious senior scientist ...
How the Proliferation of Fraudulent Scientific Papers Is Threatening the Integrity of Cancer Research
There is a perception among many scientists that scientific fraud is a rare occurrence, resulting from the actions of a few isolated bad actors. However, an extensive investigation by Reese A.K. Richardson, PhD, postdoctoral fellow at the Center for Science of Science and Innovation, Kellogg School ...
How Embedding an Algorithm-Based Referral System Into Electronic Health Records Is Increasing Access to Palliative Care
Despite numerous studies showing the benefits of integrating palliative care in both the early- and advanced-stage cancer settings,1 palliative care remains underutilized for most patients with cancer. A recent study by the American Cancer Society found that only 10% of Medicare beneficiaries with...
ESMO Publishes Guidance on Large Language Model Use for Oncology Practice
The European Society for Medical Oncology (ESMO) has released its first set of recommendations for the use of artificial intelligence (AI) large language models in oncology practice, called the ESMO Guidance on the Use of Large Language Models in Clinical Practice (ELCAP). The guidance was...
$16 Million PRISM Trial Will Explore AI in Breast Cancer Screening
The University of California, Los Angeles (UCLA) and UC Davis will co-lead a newly funded, multi-institutional clinical trial to evaluate whether artificial intelligence (AI) can help support radiologists in interpreting mammograms more accurately, with the goal of improving breast cancer screening ...
Cutaneous Squamous Cell Carcinoma: AI Model Rivals Dermatologists in Differentiation Assessment
Performance of a convolutional neural network in determining differentiation levels of cutaneous squamous cell carcinomas was on par with that of experienced dermatologists, according to the results of a recent study published in JAAD International. “This type of cancer, which is a result of...
AI Shear Wave Elastography Model for Diagnosing Breast Cancer in BI-RADS 3 or 4 Masses
In a study (INSPiRED 006) reported in the Journal of Clinical Oncology, Cai et al found that an artificial intelligence–guided shear wave elastography (AI-SWE) model provided accuracy similar to expert reading of B-mode ultrasound in the diagnosis of breast cancer in women with Breast Imaging...
How the AI-Powered ASCO® Guidelines Assistant Is Improving Clinical Decision-Making
This past May, ASCO announced its collaboration with Google Cloud to launch the ASCO® Guidelines Assistant, a new interactive tool that allows clinicians to quickly access ASCO’s evidence-based clinical guidelines to facilitate critical clinical decision-making. Developed with Google Cloud’s Vertex ...
How to Adapt to the Era of AI and the Changing Interactions With Patients: Lessons From a Low-Resource Setting
After 2 decades of practicing medicine across multiple disciplines and health systems, I’ve witnessed the dramatic transformation of patient-physician interactions, and none more dramatic than what I’m seeing in this era of artificial intelligence (AI) and its impact on cancer care. Early in my...
Hybrid AI Approach With Uncertainty Quantification for Mammography Reading Supports Safe Workload Reduction
Investigators have developed and tested a hybrid reading strategy for screening mammography images with artificial intelligence (AI) that includes reads from radiologists and a stand-alone AI interpretation of mammograms with an uncertainty quantification. According to study findings published in...
Routine AI Assistance May Lead to Loss of Skills in Endoscopists, Study Shows
The introduction of artificial intelligence (AI) to assist colonoscopies may be linked to a reduction in the ability of endoscopists to detect adenomas in the colon without AI assistance, according to a paper published by Budzyń et al in The Lancet Gastroenterology & Hepatology. Colonoscopy...
RSNA Challenge AI Models Enhance Mammography Detection of Invasive Breast Cancer
Various artificial intelligence (AI) algorithms submitted as part of a challenge demonstrated the ability to identify different breast cancers during screening mammography, according to the results of a study published in Radiology. Ensemble models of the top submitted algorithms indicated that the ...
LLM Trained on Somatic Mutations Shows Prognostic and Predictive Utility
Large language models (LLMs) can be trained to understand how each patient’s somatic mutations impact their cancer prognosis and possible response to therapy, according to a presentation at the AACR Special Conference in Cancer Research: Artificial Intelligence and Machine Learning. John-William...
AI Enhances Detection of Missed Breast Cancers on Screening Tomosynthesis
A U.S. Food and Drug Administration (FDA)–cleared artificial intelligence (AI) algorithm was able to detect and correctly localize almost one-third of interval breast cancers in a retrospective evaluation of screening digital breast tomosynthesis (DBT), findings published in Radiology showed. The...
Classifying Pancreatic Cysts Using AI Models
In a proof-of-concept study published in the Journal of the American College of Surgeons, researchers investigated whether artificial intelligence (AI) models such as ChatGPT-4 can be used to accurately extract and classify diagnostic data from radiologic imaging reports of pancreatic cysts. The...
Online AI Tool Offers Rapid, Accurate Diagnosis for Endocrine Cancers
Researchers have developed a novel AI-powered online platform for diagnosing endocrine cancers with speed and accuracy. The AI models achieved diagnostic accuracy of 99% or more in recognizing multiple endocrine tumors. Reports of the development and validation of the models were presented at ENDO...
AI-Enhanced PACT as a Noninvasive Breast Imaging Alternative
Panoramic photoacoustic computed tomography (PACT) with machine learning assistance could be a safe, noninvasive, and sensitive alternative to mammography, ultrasound, and magnetic resonance imaging (MRI) for breast cancer screening, according to study results that were published in Nature...
