Melanoma: Can AI Enable Diagnosis Prediction?
Assessment of machine-learning models tested on Swedish registry data enabled more accurate melanoma diagnosis prediction, with added health-care code, age, sex, and medication information for improved performance, according to the results of a study published in Acta Dermato-Venereologica. “Our...
AI Tool Shows Early Ability in Pinpointing Cells Driving Aggressive Cancers
Researchers have developed an artificial intelligence (AI) tool that can identify small groups of cells most responsible for driving aggressive cancers. The tool, called SIDISH, offers scientists a clearer path to designing targeted therapies by showing which cells inside a tumor are most strongly...
Large Language Models May Generate Concise, Coherent Pathology Summaries, Reducing Physician Burden
Large language models performed better than physicians at producing accurate and comprehensive oncology pathology report summaries, according to the results of a study published in JCO Clinical Cancer Informatics. Six large language models were tested in the study, and most generated summaries...
Prompting Strategies May Improve Symptom Monitoring in Childhood Cancer Survivors
Prompting strategies on two large language models improved how the artificial intelligence (AI) interpreted pain and fatigue reported by survivors of childhood cancers for better symptom monitoring and care, according to findings published in Communications Medicine. The study authors noted that...
AI Shows Dermatologist-Level Accuracy in Melanoma Diagnosis but Needs Validation
In a systematic review and meta-analysis published in JAMA Dermatology, Laiouar-Pedari et al evaluated the real-world diagnostic performance of artificial intelligence (AI)–assisted dermoscopy for melanoma detection. The study was undertaken to address a critical gap in the literature: while prior...
Machine-Learning Model for HCC Risk Prediction May Outperform Current Methods
An interpretable machine-learning framework, called PRE-Screen-HCC, may predict risk levels for developing hepatocellular carcinoma (HCC) more accurately than publicly available risk scores, according to findings from a large population-based multicentric study published in Cancer Discovery. “Our...
AI-Driven Multiagent System for Guiding First-Line Immunotherapy for NSCLC
An artificial intelligence (AI) multiagent system demonstrated correct and complete reasoning in determining the use of immunotherapy for patients with non–small cell lung cancer (NSCLC) in the first-line setting, according to findings presented during the first European Society for Medical...
AI Model for Predicting Oncotype DX 21-Gene Recurrence Score
As reported in The Lancet Oncology, Shamai et al have developed an artifical intelligence (AI) model based on digital histopathology slide images and clinical features to predict the Oncotype DX 21-gene recurrence score (RS) in patients with hormone receptor–positive, HER2-negative invasive breast...
AI As Collaborator in Cancer Research and in Clinical Care
Last October, the Cancer AI Alliance (CAIA) announced the launch of its collaborative artificial intelligence (AI) platform powered by federated learning to train AI models with millions of de-identified patient datasets from participating cancer centers, while maintaining patient security,...
AI Use in Cancer Diagnosis, Prognosis, and Treatment: Are We There Yet?
The promise of artificial intelligence (AI) technologies to provide highly personalized oncology care for patients and improve outcomes has been decades in the making. In a 1987 editorial in The New England Journal of Medicine, pioneering nephrologist and health economist William B. Schwartz, MD,...
Using AI to Differentiate Primary Lung Squamous Cell Carcinomas From Metastases
A multipronged artificial intelligence (AI)–assisted approach integrated into routine molecular profiling identified 3.1% of cases submitted as lung squamous cell carcinoma as metastases from other origins, revealing a meaningful rate of misdiagnosis in this patient population, according to a...
How AI Is Already Having a Significant Impact on Cancer Care
Three education sessions presented during the 2025 ASCO Annual Meeting showcased how artificial intelligence (AI) is quickly transforming cancer care from clinical trial planning and ambient scribes transcribing physician-patient conversations to therapeutic decision-making. The meeting also...
Three AI-Enabled Analyses Highlight Context-Dependent Biomarkers in Early-Onset Colorectal Cancer
Biomarker discovery in colorectal cancer has traditionally focused on identifying molecular alterations with broad prognostic or predictive utility. However, evidence is increasingly suggesting that biomarkers do not have universal prognostic or predictive value across patient sets but instead...
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...
