Advertisement

Advertisement

Pancreatic Cancer
AI in Oncology

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...

Breast Cancer
AI in Oncology

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...

Lung Cancer
AI in Oncology

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 in Oncology

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...

Breast Cancer
AI in Oncology

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...

AI in Oncology

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...

AI in Oncology

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...

ai in oncology

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 ...

AI in Oncology
CNS Cancers

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...

Breast Cancer
AI in Oncology

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% ...

AI in Oncology

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 ...

Issues in Oncology
AI in Oncology

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 ...

Palliative Care
AI in Oncology

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...

Issues in Oncology
AI in Oncology

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...

Breast Cancer
AI in Oncology

$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 ...

Skin Cancer
AI in Oncology

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...

Breast Cancer
AI in Oncology

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...

Issues in Oncology
AI in Oncology

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 ...

AI in Oncology

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...

Colorectal Cancer
Issues in Oncology
AI in Oncology

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...

Breast Cancer
AI in Oncology

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 ...

Genomics/Genetics
AI in Oncology

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...

Issues in Oncology
AI in Oncology
Pancreatic Cancer

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...

Thyroid Cancer
Neuroendocrine Tumors
AI in Oncology

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...

Breast Cancer
AI in Oncology

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...

Issues in Oncology
AI in Oncology

Study Finds AI Chatbots Are Vulnerable to Spreading Malicious, False Health Information

While artificial intelligence (AI) large language models (LLMs) hold the promise to help consumers find trustworthy health information, a study assessing the safeguards incorporated into these models has found that they are vulnerable to malicious instruction that converts them into health...

Sarcoma
AI in Oncology

Digital Histopathology and Automated Classification of Pediatric Sarcomas

With more than 50 different subtypes, pediatric soft-tissue sarcomas represent a broad category of disease. And given the rarity of these sarcomas, “it is difficult for pathologists to see a sufficient volume to gain expertise across all variants,” stated Adam Thiesen, BA, MD/PhD Candidate at UConn ...

Skin Cancer
AI in Oncology

Pathology Machine-Learning Models and Diagnosis of Nonmelanoma Skin Cancers in Resource-Limited Settings

Artificial intelligence (AI) models, which were pretrained on vast data sets, outperformed a standard baseline model in identifying nonmelanoma skin cancers from digital images of tissue samples, based on a session presented during the 2025 American Association for Cancer Research (AACR) Annual...

Breast Cancer
AI in Oncology

Study Shows Potential Benefits of AI-Assisted Classification in HER2-Low and HER2-Ultralow Breast Cancer

With the approval of HER2-targeted antibody-drug conjugate options for treating patients with breast cancer across different HER2 expression levels, accurate assessment of HER2 expression has become more important than ever. And a recent study may provide a solution to the challenge of accurate...

prostate cancer
ai in oncology

Nicholas D. James, PhD, FRCP, MBBS, on Using AI to Identify Benefit From Prostate Cancer Therapy

Nicholas D. James, PhD, FRCP, MBBS, of The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, describes the use of a multimodal artificial intelligence (AI) model to identify benefit from second-generation androgen receptor pathway inhibitors in patients with high-risk nonmetastatic prostate cancer participating in the STAMPEDE trial (Abstract 5001).   

ai in oncology

Clifford A. Hudis, MD, FASCO, FACP, on ASCO Guidelines Assistant

Clifford A. Hudis, MD, FASCO, FACP, Chief Executive Officer of ASCO, discusses ASCO Guidelines Assistant, an AI-based collaboration between ASCO and Google Cloud which draws from ASCO’s evidence-based, published clinical practice guidelines, offering clinicians ready access to timely, trustworthy information.

Breast Cancer
AI in Oncology

Use of AI Assistance to Improve HER2 Breast Cancer Classifications

The accuracy of HER2 breast cancer scoring improved with the use of AI assistance, especially for patients with low and ultralow levels of HER2 expression, results from a multinational study showed. The findings were presented in a press briefing ahead of the 2025 ASCO Annual Meeting (Abstract...

AI in Oncology

ASCO and Google Cloud Announce AI-Powered Tool That Provides Faster, Interactive Access to ASCO’s Evidence-Based Clinical Guidelines

ASCO and Google Cloud have announced a collaboration to launch an artificial intelligence (AI)-based ASCO Guidelines Assistant. Developed with Google Cloud’s Vertex AI platform and Gemini models, the tool is poised to transform how oncology professionals access and use critical clinical...

Palliative Care
AI in Oncology

AI Model Estimates Biological Age and Predicts Survival in Patients With Cancer

FaceAge, a deep learning system, was developed and validated to estimate biological age from photographs of faces. In a study published in The Lancet Digital Health, FaceAge showed the ability to predict short-term outcomes in patients with cancer.   The study demonstrated that FaceAge could...

Breast Cancer
Issues in Oncology
AI in Oncology

Collaborative Strategy Involving AI, Human Task-Sharing Could Help Minimize Mammogram Costs

When screening for breast cancer, the most effective strategy to utilize artificial intelligence (AI) may involve collaboration with human radiologists, according to a recent study published by Ahsen et al in Nature Communications. The findings could help shape how hospitals and clinics integrate...

Advertisement

Advertisement

Advertisement