AI and Cancer

Researchers have discovered that cancer spread isn’t random—it follows a kind of biological “program.” By studying colon tumor cells, they identified gene patterns that signal whether a cancer is likely to metastasize. Their AI model, MangroveGS, can predict this risk with about 80% accuracy and even works across multiple cancer types. This could transform how doctors decide who needs aggressive treatment and who doesn’t.

Increasing use of blood tests to detect prostate cancer is leading to overworked doctors. NTNU has now created an AI diagnostic tool that can help lighten the burden.

Cancer often begins when the genetic instructions that guide our cells become scrambled, allowing cells to grow uncontrollably. Now, scientists at EMBL have developed an AI-powered system called MAGIC that can automatically spot and tag cells showing early signs of chromosomal trouble—tiny DNA-filled structures known as micronuclei that are linked to future cancer development.

Researchers evaluated four deep learning models using over 112,000 negative screening mammograms from the UK NHS to determine how well artificial intelligence could predict future breast cancers missed during routine screening. The MIT-developed Mirai model performed best, identifying about 27.5% of interval cancers within the top 4% of women flagged as highest risk.

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New research warns that popular deep learning systems trained for cancer pathology may be relying on hidden shortcuts rather than genuine biological signals.

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Using machine learning, an electronic nose can "smell" early signs of ovarian cancer in the blood. The method is precise and, according to the LiU researchers behind the study, it could eventually be used to find many different cancers. The study is published in the scientific journal Advanced intelligent systems.

An international research team, with significant involvement from the Medical University of Vienna, has developed a new AI-based analysis method that can accurately classify brain tumors using genetic material from cerebrospinal fluid (CSF) and monitor the progression of the disease.

People with ulcerative colitis (UC), a chronic inflammatory bowel disease, are up to four times more likely to develop colorectal cancer than the general population.

Today, many men must choose between life-altering prostate removal or careful long-term monitoring. The EU-funded ROBIOSPY Project offers an intermediate option: precise needle-based diagnostics and targeted therapy powered by AI-driven robotics.

Eyonis LCS aids in both detecting and characterizing nodules, distinguishing it from its many competitors.

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A clinical trial shows that AI-assisted mammography can detect more cases of dangerous cancer and reduce missed diagnoses.

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The NHS has launched an AI and robot pilot to help spot lung cancer sooner, as well as a screening program that aims to help tackle inequalities in cancer.

University researchers have pioneered a new tool to determine the risk of secondary heart attacks in cancer patients using Artificial Intelligence.

Jan. 31, 2026: Our weekly roundup of the latest science in the news, as well as a few fascinating articles to keep you entertained over the weekend.

Cancer patients who suffer a heart attack face a dangerous mix of risks, which makes their clinical treatment particularly challenging.

FRIDAY, Jan. 30, 2026 — Artificial intelligence (AI) can help reduce the number of breast cancers found between mammogram screenings, clinical trial results show.There was a 12% reduction in cancer diagnoses in the years following AI-supported b...

Artificial intelligence (AI)-supported mammography identifies more cancers during screening and reduces the rate of breast cancer diagnosis by 12% in the years following, finds the first randomised controlled trial of its kind involving over 100,000 Swedish women published in The Lancet journal.

Interval cancers are aggressive tumours that grow during the interval after someone has been screened for cancer and before they are screened again, and AI seems to be able to identify them at an early stage

England's National Health Service trials of a new artificial intelligence and robotics technology for lung cancer detection is set to go underway.

Why do some tumors spread while others remain localized? The mechanisms governing the metastatic potential of tumor cells remain largely unknown — yet understanding this is crucial for optimizing patient care.

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Researchers have turned artificial intelligence into a powerful new lens for understanding why cancer survival rates differ so dramatically around the world. By analyzing cancer data and health system information from 185 countries, the AI model highlights which factors, such as access to radiotherapy, universal health coverage, and economic strength, are most closely linked to better survival in each nation.

A new and important discovery comes from the field of oncological research thanks to the joint work of researchers from the Sbarro Institute in Philadelphia, the National Cancer Institute – Pascale Foundation, and the University of Pisa.

Aston Sci. Inc., a clinical-stage biopharmaceutical company pioneering next-generation therapeutic cancer vaccines, announced today that it has implemented CDD Vault®, the secure, cloud-based research informatics platform from Collaborative Drug Discovery (CDD).

Mayo Clinic researchers have developed and evaluated MedEduChat, an electronic health record (EHR) that works with a large language model to provide accurate, patient-specific prostate cancer education.

Detecting cancer in the earliest stages could dramatically reduce cancer deaths because cancers are usually easier to treat when caught early.

Thyroid cancer is the most common endocrine cancer, affecting more people each year as detection rates continue to rise.

Nanoparticles coated with molecular sensors could be used to develop at-home tests for many types of cancer.

Detecting cancer in the earliest stages could dramatically reduce cancer deaths because cancers are usually easier to treat when caught early. To help achieve that goal, MIT and Microsoft researchers are using artificial intelligence to design molecular sensors for early detection.

Google's AI search summaries are giving dangerous health advice, from telling pancreatic cancer patients to avoid fats to misreporting liver test results, misleading users and prompting serious risks.

AI tools designed to diagnose cancer from tissue samples are quietly learning more than just disease patterns. New research shows these systems can infer patient demographics from pathology slides, leading to biased results for certain groups. The bias stems from how the models are trained and the data they see, not just from missing samples. Researchers also demonstrated a way to significantly reduce these disparities.

Pathology has long been the cornerstone of cancer diagnosis and treatment. A pathologist carefully examines an ultrathin slice of human tissue under a microscope for clues that indicate the presence, type, and stage of cancer.

Insilico Medicine has developed a new class of small molecule inhibitors targeting diacylglycerol kinase alpha (DGKα) designed to restore T cell function and overcome resistance to immune checkpoint blockades in solid cancers.

In recent years AI has emerged as a powerful tool for analyzing medical images. Thanks to advances in computing and large medical datasets from which AI can learn, it has proven to be a valuable aid in reading and analyzing patterns in X-rays, MRIs and CT scans, enabling doctors to make better and faster decisions, particularly in the treatment and diagnosis of life-threatening diseases like cancer.

"This is the miracle of AI. We can actually manufacture intelligence."

A large study shows that routine H&E pathology slides contain rich spatial proteomic signals that can be decoded by AI to model the tumor immune microenvironment at population scale. By generating virtual multiplex immunofluorescence images, GigaTIME enables pan-cancer discovery of immune patterns linked to invasion stage, survival, and genomic alterations.

An artificial intelligence (AI) model created by integrating clinical, molecular, and histopathological data significantly improved recurrence risk stratification in hormone receptor (HR)-positive, HER2-negative breast cancer, according to results presented at the San Antonio Breast Cancer Symposium (SABCS), held December 9-12, 2025.

University of South Australia scientists have developed a powerful new way to uncover the genetic interactions that fuel cancer progression, paving the way for earlier and more precise treatments.

New research on public attitudes toward AI indicates that most people are reluctant to let ChatGPT and other AI tools diagnose their health condition, but see promise in technologies that use AI to help diagnose cancer.

In preclinical studies, D16-M1P2 showed consistent potency in -amplified breast cancer cell lines and in an -mutant cholangiocarcinoma (bile duct cancer) line, as well as in a -amplified breast cancer xenograft model. The post Insilico Details AI-Designed, Cancer-Fighting PROTAC Targeting PKMYT1 appeared first on GEN - Genetic Engineering and Biotechnology News.

While targeted radiation can be an effective treatment for brain tumors, subsequent potential necrosis of the treated areas can be hard to distinguish from the tumors on a standard MRI.

A recent study reveals that integrating Artificial Intelligence (AI) into colon cancer diagnosis over the past five years has significantly improved the speed and accuracy of the detection of the deadly disease.

The prospect of diagnosing cancer through painless methods—such as a simple AI-assisted blood or urine test that detects tiny particles known as exosomes—is becoming increasingly realistic.

An image-only artificial intelligence (AI) model for predicting the five-year risk of breast cancer provided stronger and more precise risk stratification than breast density assessment, according to a new study being presented next week at the annual meeting of the Radiological Society of North America (RSNA).

Complex digital images of tissue samples that can take an experienced pathologist up to 20 minutes to annotate

When doctors told her they had to remove her tongue and voice box to save her life from the cancer that had invaded her mouth, Sonya Sotinsky sat down with a microphone to record herself saying the things she would never again be able to say.

A new paper shows ChatGPT-5 emerging as a tool that helps scientists test ideas, navigate literature and refine experiments

Five artificial intelligence systems designed to detect polyps during colonoscopies have received conditional recommendation from NICE.

Artificial intelligence (AI) can predict how well patients with rectal cancer will respond to treatment by analyzing standard tissue samples taken during diagnosis, finds a new study from researchers at UCL and UCLH.

After enduring seven prior abdominal surgeries, 64-year-old Joy Monetti from Islip was no stranger to painful procedures and lengthy recoveries.

Magnetic soft robots deliver and release tens of millions of probiotic bacteria with timed control, disrupt tumor spheroids in vitro, and demonstrate a potential strategy for targeted cancer treatment.

The study is set to determine whether AI is capable of helping doctors in making better treatment decisions for prostate cancer

Artificial intelligence (AI) is fundamentally reshaping the landscape of solid tumor (ST) drug development.

In a study of more than 100,000 screening mammograms, researchers demonstrated the potential of an AI tool to help identify women at higher risk of developing interval breast cancers, breast cancer that is diagnosed between regular screening mammograms.

A new NHS pilot using AI to interpret MRI scans could fast-track prostate cancer diagnosis, reducing waiting times and easing radiologist workloads.

UK researchers are testing an AI-enhanced breast imaging tool that could improve cancer detection rates in women with dense breast tissue.

The United States government has struck a $1 billion deal with Advanced Micro Devices (AMD) to build two

Scientists at University of California San Diego have developed a new approach to destroying cancer stem cells – hard-to-find cells that help cancers spread, come back after treatment and resist therapy.

Researchers developed an AI strategy, CANDiT, that identifies, reprograms and ultimately triggers colon cancer stem cells to self-destruct. The team suggests the ability to track and selectively kill CSCs brings scientists “closer to rewriting the rules of cancer treatment.” The post AI Treatment Reprograms and Triggers Cancer Stem Cells to Self-Destruct appeared first on GEN - Genetic Engineering and Biotechnology News.

Iambic Therapeutics said on Monday early-stage data of its experimental drug showed anti-tumor activity in heavily pretreated cancer patients with mutations in the HER2...

Research reveals AI's role in cervical cancer detection in underserved regions, emphasizing the importance of community trust and healthcare investment.

An innovative biotech startup founded by researchers at Washington University School of Medicine in St. Louis has been acquired by Lunit, a leading company in developing AI-based technologies for cancer prevention and early detection.

AI can be used to detect cervical cancer in women in resource-limited parts of the world. However, for this method to work, investments are needed in healthcare staff, reliable supply chains and trust in these communities.

A Harvard Medical School–led research team has developed an AI tool that can reliably tell apart two look-alike

A new AI tool called DOLPHIN exposes hidden genetic markers inside single cells, enabling earlier detection and more precise treatment choices. It also sets the stage for building virtual models of cells to simulate disease and drug responses.

TUESDAY, Sept. 30, 2025 — A cutting-edge robot-assisted bronchoscope can reach very small tumors growing in the lung’s deepest recesses, according to clinical trial results presented at a European Respiratory Society meeting in Amsterdam.The device...

A new national initiative aims to use AI-based models to improve the diagnosis and treatment of cancer patients.

A cutting-edge bronchoscope that is guided with the help of a robot can reach very small tumors growing in hard-to-reach parts of the lung, according to results of a gold-standard randomized-controlled trial that will be presented at the European Respiratory Society (ERS) Congress in Amsterdam, the Netherlands.

Sylvester Comprehensive Cancer Center, part of University of Miami Miller School of Medicine, 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 and reducing unnecessary callbacks and anxiety for patients.

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 and reducing unnecessary callbacks and anxiety for patients.

Integration of AI into cancer care appears limited to certain fields but that may change if the technology realizes its potential of personalizing risk assessment and treatment, experts say.

Attitudes toward the use of AI in health care were split 50/50, according to a recent survey conducted by the Cancer Support Community.

AI can do more than just write your essays - a new model is advancing drug discovery for hard-to-treat diseases.

A new method can produce custom-designed proteins in just 4-6 weeks that can arm the T cells of

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer.

An international, interdisciplinary research team led by Prof. Jakob N. Kather from the Else Kröner Fresenius Center (EKFZ) for Digital Health at TUD Dresden University of Technology analyzed seven independent patient cohorts from Europe and the USA using their newly developed AI model.

Two studies led by Johns Hopkins Kimmel Cancer Center, Ludwig Center, and Johns Hopkins Whiting School of Engineering researchers report on a powerful new method that significantly improves the reliability and accuracy of artificial intelligence (AI) for many applications. As an example, they apply the new method to early cancer detection from blood samples, known as liquid biopsy.

Cancer patients can regain full health with immunotherapy. Now researchers are hunting for the perfect immune cell with the help of a very special robot.

Outcomes favoring robotic surgery for CRC may be influenced by patient selection factors, including clinical stability.

An AI system can identify high-risk areas on interval breast cancer screening mammograms and detect tumours that radiologists miss, a Swiss study shows.

AI is detecting tumors more often and earlier in the Dutch breast cancer screening program. Those tumors can then be treated at an earlier stage.

The FDA’s De Novo authorization for the tool establishes a new product code category for future AI-powered digital pathology risk-stratification tools.

AI is not benign.

Continuing its transformation since joining NYU Langone Health, the operative team at NYU Langone Hospital—Suffolk recently performed four complex robotic surgeries that had never been offered at the facility before, three of which successfully removed cancerous tumors from patients.

During magnetic resonance imaging (MRI) procedures, contrast agents, such as the rare metal gadolinium, can pose potential health risks.

WEDNESDAY, Aug. 13, 2025 — A person’s own voice might soon be a means of detecting whether they’re suffering throat cancer, a new study says.Men with cancer of the larynx, or voice box, have distinct differences in their voices that could be detec...

Algorithms submitted for an AI Challenge hosted by the Radiological Society of North America (RSNA) have shown excellent performance for detecting breast cancers on mammography images, increasing screening sensitivity while maintaining low recall rates, according to a study published today in Radiology, the premier journal of the RSNA.

Cancer of the voice box or larynx is an important public health burden. In 2021, there were an estimated 1.1 million cases of laryngeal cancer worldwide, and approximately 100,000 people died from it. Risk factors include smoking, alcohol abuse, and infection with human papillomavirus.

Traditional drug development methods involve identifying a target protein (e.g., a cancer cell receptor) that causes disease, and then searching through countless molecular candidates (potential drugs) that could bind to that protein and block its function. This process is costly, time-consuming, and has a low success rate.