The Thymus Plays a Part in Adult Cancer Risk and Treatment Response, Research Reveals
Two papers published in Nature reveal long-disregarded functions of the thymus in adulthood, showing that the overall health of the organ impacts aging and risks for cardiovascular disease and cancer, as well as affecting response to immunotherapy in patients with cancer. “The thymus has been...
AMA Survey Finds Rapid Growth in Physician AI Adoption
The 2026 Physician Survey on Augmented Intelligence from the American Medical Association’s (AMA) Center for Digital Health and AI indicates that physician adoption of AI is increasing alongside growing confidence in the technology’s ability to address clinical challenges. This annual survey on...
AI Integration in Breast Cancer Screening Increases Detection Rate, Reduces Work Burden
Integration of artificial intelligence (AI) into screening workflows increased the detection of breast cancer by 10.4% in the United Kingdom, according to the results of the GEMINI study published in Nature Cancer. Additionally, use of AI in different workflows led to reductions in workload by up...
AI-Backed Liquid Biopsies Identify Liver Diseases
Building upon the foundation of liquid biopsy utility for the early detection of cancer, analysis of genome-wide cell-free DNA fragmentation with machine learning classification and modeling can also extend to the identification of liver cirrhosis and other chronic diseases, according to findings...
Accuracy of Molecular Inference–Based AI Model for CNS Tumor Diagnosis
In a retrospective study reported in The Lancet Oncology, Lalchungnunga et al tested the classification accuracy of a molecular inference–based artificial intelligence (AI) model (Neuropath-AI) in central nervous system (CNS) tumor diagnosis. Study Details The multi-institutional study included...
Research Suggests AI Pathology Models May Take Unreliable 'Shortcuts' to Identify Cancer Biomarkers
Artificial intelligence (AI) tools that detect molecular biomarker status from histologic images may be dependent upon correlational relationships with clinicopathologic features, preventing the models from learning the true causal effect of the biomarker, according to findings published in Nature...
AI Model May Predict Cancer Risk in Patients With Colitis-Associated Low-Grade Dysplasia
In a new study published in Clinical Gastroenterology and Hepatology, Johnson et al reported that an automated artificial intelligence (AI) pipeline using large language models (LLMs) can accurately stratify future risk of advanced neoplasia in patients with colitis-associated low-grade dysplasia....
Medical Societies and More Respond to HHS RFI on AI Use in Clinical Care
In time for the assigned deadline of February 23, 2026, medical societies, companies, health-care systems, and more have responded to a request for information from the Department of Health and Human Services (HHS) regarding the use of artificial intelligence (AI) in clinical practice. The Request...
Anna Clare Wilkins, PhD, MRCP, MBBChir, on Localized Prostate Cancer: MMAI-Derived Biomarker
Anna Clare Wilkins, PhD, MRCP, MBBChir, of The Institute of Cancer Research, discusses the external validation of a digital pathology-based multimodal artificial intelligence (MMAI)-derived prognostic biomarker using data from the phase III CHHiP trial. CHHiP evaluated conventional vs hypofractionated high-dose intensity-modulated radiotherapy for patients with localized prostate cancer (Abstract 308).
Lung Cancer: Variability of Open-Source AI Models in EGFR Mutation Prediction
In a study reported in JAMA Oncology, Rakaee et al identified the accuracy of open-source artificial intelligence (AI) models in predicting the presence of EGFR mutations in samples from patients with lung adenocarcinoma, including according to ancestral subgroups. Study Details The study included...
I Used AI to Supplement My Oncology Care—It Reshaped My Treatment Plan
A year ago, I was confronting a series of symptoms—including rapid weight loss, abdominal distress, fatigue, and heart issues—that I couldn’t explain. I was just 60 years old and had been in good health, but now I sensed that something was seriously wrong. I made appointments with my primary care...
Introducing ASCO AI in Oncology
In February, ASCO and Conexiant launched ASCO AI in Oncology (ascoai.org), a digital platform dedicated to understanding how artificial intelligence (AI) is impacting cancer care. “Our goal with this hub is to empower oncology professionals with knowledge and the tools to adapt to a rapidly...
AI-Selected Biomarker Guides First-Line Treatment Selection in Advanced Pancreatic Cancer
A computational histology–based artificial intelligence (AI) platform was able to identify a biomarker that could predict treatment benefit between two chemotherapy options for patients with advanced pancreatic cancer, according to the results of a study presented in a poster at the 2026 ASCO...
AI Tool Classifies Pediatric Brain Tumors via Liquid Biopsy
Researchers developed a deep neural network, M-PACT, to identify and classify brain tumors in pediatric patients from the subnanogram-input cell-free DNA of methylomes, according to findings published in Nature Cancer. “This is a next-generation assay and computational framework that we’ve...
Computational Histology Artificial Intelligence–Powered Biomarker for Selection of Chemotherapy in Advanced Pancreatic Cancer
In a study reported in the Journal of Clinical Oncology, Hendifar et al found that a computational histology artificial intelligence (CHAI)-powered platform could be used to identify whether gemcitabine-based (G-chemo) or fluoropyrimidine-based (F-chemo) chemotherapy is preferred as first-line...
Interval Cancer Rate With AI-Supported Mammography Screening
In a Swedish trial (MASAI) reported in The Lancet, Gommers et al found that artificial intelligence (AI)-supported mammography was noninferior to standard double reading without AI in identifying interval breast cancers in women undergoing breast cancer screening. Study Details In the study,...
ASCO and Conexiant Launch ASCO AI in Oncology
The American Society of Clinical Oncology (ASCO®) and Conexiant today announced the launch of ASCO AI in Oncology, a premier digital destination designed to help oncology professionals navigate the transformative role of artificial intelligence (AI) in cancer care. Launching this initiative marks...
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% ...
