AI and Cancer

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.

One in every three people is expected to have cancer in their lifetime, making it a major health concern for mankind.

What if a computer could read a patient's medical notes and help doctors determine important information for their treatment?

Skin cancer is the most common form of cancer worldwide, and early detection is key to successful treatment.

An AI algorithm for breast cancer screening has potential to enhance the performance of digital breast tomosynthesis (DBT), reducing interval cancers by up to one-third, according to a study published today in Radiology, a journal of the Radiological Society of North America.

A team of scientists has developed a remarkable new approach to modeling how cells behave over time—using a digital "forecast" much like predicting the weather. By combining patient genomics with a groundbreaking plain-language “hypothesis grammar,” the researchers can simulate how cells communicate and evolve within tissues. These simulations allow scientists to digitally test how cancers grow, how immune systems respond, and even how treatments might work in individual patients.

A new artificial intelligence model can improve the process of drug and vaccine discovery by predicting how efficiently specific mRNA sequences will produce proteins, both generally and in various cell types.

A new artificial intelligence model can improve the process of drug and vaccine discovery by predicting how efficiently specific mRNA sequences will produce proteins, both generally and in various cell types.

A breakthrough AI system is revolutionizing cancer immunotherapy by enabling scientists to design protein-based keys that train a patient s immune cells to attack cancer with extreme precision. This method, capable of reducing development time from years to weeks, was successfully tested on known and patient-specific tumor targets. Using virtual safety screenings to avoid harmful side effects, the platform represents a leap forward in personalized medicine.

Precision cancer treatment on a larger scale is moving closer after researchers have developed an AI platform that can tailor protein components and arm the patient's immune cells to fight cancer.

A new AI tool opens the door for designer protein drugs that tackle pain, cancer, and brain diseases. The post AI-Designed Drugs Can Now Target Previously ‘Undruggable’ Proteins in Cancer and Alzheimer’s appeared first on SingularityHub.

Cure-in Inc. (co-CEOs Yung-Ho Jo and Samuel Byeongjun Park), a medical robotics company founded in 2020 by a research team from the Department of Biomedical Engineering at the National Cancer Center, aims to offer trust to medical professionals and comfort to patients.

AI support enhances radiologists' accuracy in breast cancer detection during mammograms, improving focus on high-risk areas without increasing reading time.

Estimating the cell type composition in a tissue sample using bulk data is a major challenge in cancer research. OmicsTweezer integrates complex biological datasets to provide a clearer, more accurate view of the tumor microenvironment. The post AI-Powered Tool, OmicsTweezer, Enhances Tumor Tissue Analysis appeared first on GEN - Genetic Engineering and Biotechnology News.

As cancer cases have increased worldwide, the disease has become more complex, presenting challenges to scientific advances in diagnosis and treatment.

An AI model trained to detect abnormalities on breast MR images accurately depicted tumor locations and outperformed benchmark models when tested in three different groups, according to a study published today in Radiology, a journal of the Radiological Society of North America (RSNA).

A novel artificial intelligence (AI) application capable of diagnosing endocrine cancers with speed and accuracy is being presented Sunday at ENDO 2025, the Endocrine Society's annual meeting in San Francisco, Calif.

Use of TumorSight Viz may support improved consistency, precision, and efficiency in breast cancer surgery.

Quibim, a global leader in quantitative medical imaging solutions, today announced that its flagship solution, QP-Prostate, has been selected for a major NHS-backed rollout aimed at improving early detection of prostate cancer across seven hospitals in England.

“Developments that take high-dimensional data and come up with interpretable insights…are going to play an increasing role,” says Smita Krishnaswamy, PhD.

Artificial intelligence is now designing custom proteins in seconds—a process that once took years—paving the way for cures to diseases like cancer and antibiotic-resistant infections. Australian scientists have joined this biomedical frontier by creating bacteria-killing proteins with AI. Their new platform, built by a team of biologists and computer scientists, is part of a global movement to democratize and accelerate protein design for medical breakthroughs.

Dr. Ho Sang Jung and his research team from the Advanced Bio and Healthcare Materials Research Division at the Korea Institute of Materials Science(KIMS) have developed an optical biosensor capable of detecting trace amounts of cancer cell DNA in the bloodstream with high sensitivity, enabling early cancer diagnosis.

In this multi-year technology and research collaboration, Revolution Medicine’s proprietary data will train a bespoke version of NeuralPLexer, Iambic’s AI model for protein-ligand structure prediction, to discover novel cancer drug candidates.  The post Iambic and Revolution Medicines Partner on AI Cancer Drug Discovery appeared first on GEN - Genetic Engineering and Biotechnology News.

Caltech's innovative PACT technique leverages AI and ultrasound for precise breast cancer detection, addressing limitations of traditional screening methods.

Pathologists' examinations of tissue samples from skin cancer tumors improved when they were assisted by an AI tool. The assessments became more consistent and patients' prognoses were described more accurately.

A pretrained artificial intelligence model demonstrates a high sensitivity in detecting pancreatic cancer on CT scans, a new study finds.

Oncologists utilizing Artificial Intelligence (AI) in their tests to spot pancreatic cancer at an early stage can also gain an overall picture of how the deadly disease is bound to develop, scientists from the University of Sharjah have revealed in a new study.

Prostate cancer is one of the most common malignancies in men globally. Hormonal therapies targeting the androgen–androgen receptor axis have significantly delayed disease progression. However, drug resistance remains inevitable, and new therapeutic targets and strategies are required to overcome androgen receptor pathway inhibitor (ARPI) resistance.

Use of the novel artificial intelligence–based test may provide a painless, low-cost alternative in bladder cancer screening.

In radiation therapy, precision can save lives. Oncologists must carefully map the size and location of a tumor before delivering high-dose radiation to destroy cancer cells while sparing healthy tissue.

An AI system called iSeg is reshaping radiation oncology by automatically outlining lung tumors in 3D as they shift with each breath. Trained on scans from nine hospitals, the tool matched expert clinicians, flagged cancer zones some missed, and could speed up treatment planning while reducing deadly oversights.

Insilico Medicine, a clinical-stage biotechnology company driven by generative artificial intelligence (AI), today announces that the first patient has been dosed in a global multicenter clinical trial (NCT06414460) to evaluate ISM3412, a potentially best-in-class, AI-empowered MAT2A inhibitor with novel structure, in patients with locally advanced and metastatic solid tumors.

A new AI tool, AAnet, has discovered five distinct cell types within tumors, offering a deeper look into cancer's inner diversity. This insight could transform how we treat cancer, enabling more personalized therapies that tackle every type of cell in a tumor.

A multinational team of researchers, co-led by the Garvan Institute of Medical Research, has developed and tested a new AI tool to better characterize the diversity of individual cells within tumors, opening doors for more targeted therapies for patients.

Imagine a stadium packed with 75,000 fans, all wearing green and white jerseys—except one person in a solid green shirt. Finding that person would be tough. That's how hard it is for scientists to find disease markers—called biomarkers—in the blood. And instead of one stadium, researchers must search through the equivalent of 100,000 stadiums worth of information.

Robotic-assisted thoracic surgery is a safe and feasible option for patients aged 80 years or older with lung cancer, demonstrating similar outcomes as in younger patients.

AI assistance is associated with a superior improvement in detecting clinically significant prostate cancer on MRI, a diagnostic study finds.

WEDNESDAY, June 18, 2025 — An experimental AI tool can help speed detection of melanoma and other skin diseases, a new study says.The tool, PanDerm, improved accuracy of skin cancer diagnoses by 11% when used by doctors, researchers reported r...

Using a blood test that requires 8-10 vials, Ultrahuman Blood Vision will deliver an assessment on your markers for cancer, fatigue, and other longevity signals.

Researchers at VCU Massey Comprehensive Cancer Center have developed a novel algorithm that could provide a revolutionary tool for determining the best options for patients - both in the treatment of cancer and in the prescription of medicines.

Fragle, an AI-based technique, revolutionizes cancer tracking through blood tests, offering faster, cheaper, and more accurate monitoring of treatment response.

The MRI image shows a brain tumor in an inauspicious location, – and a brain biopsy will entail high risks for the patient, who had consulted us due to double vision.

FRIDAY, June 6, 2025 -- The U.S. Food and Drug Administration has granted de novo authorization to CLAIRITY BREAST, a first-in-class, image-based platform that can help predict a woman's risk for breast cancer. CLAIRITY BREAST is designed as a...

Imagine diagnosing cancer not with a supercomputer but on an ordinary laptop instead. Sounds like science fiction? Thanks to a revolutionary artificial intelligence (AI) model developed by Professor Kenji Suzuki and his research team from Institute of Science Tokyo (Science Tokyo), this far-fetched scenario is now a reality.

An AI-enabled handheld ESS device, which differentiates between benign and malignant tissue, helps PCPs improve their sensitivity in diagnosing and managing skin cancer.

An 'AI scientist', working in collaboration with human scientists, has found that combinations of cheap and safe drugs – used to treat conditions such as high cholesterol and alcohol dependence – could also be effective at treating cancer, a promising new approach to drug discovery.

In a large Norwegian study, a commercial AI tool analyzed routine mammograms and identified women at elevated risk of developing breast cancer up to 4–6 years before diagnosis. These AI-generated risk scores may help personalize breast cancer screening and facilitate earlier interventions.

Clairity, Inc., a digital health innovator advancing AI-driven healthcare solutions, has received U.S. Food and Drug Administration (FDA) De Novo authorization for CLAIRITY BREAST, a novel, image-based prognostic platform designed to predict five-year breast cancer risk from a routine screening mammogram.

Camizestrant and continued CDK4/6 inhibition delayed time to QOL deterioration vs SOC therapy in ER+/HER2– advanced breast cancer.

A new artificial intelligence (AI) test can identify which men with prostate cancer will benefit most from the life-extending drug abiraterone, in clinical trial results presented by scientists from UCL and the Institute of Cancer Research.

WEDNESDAY, May 28, 2025 -- Thanks to artificial intelligence (AI), more women might soon benefit from targeted breast cancer treatment, a new study says.AI can help identify women who might be helped by cancer therapies that target HER2, a protein...

An artificial intelligence technique for detecting DNA fragments shed by tumors and circulating in a patient's blood could help clinicians more quickly identify and determine if pancreatic cancer therapies are working.

AI-assisted training dramatically reduced HER2-null overscoring and improved sensitivity in HER2-low and HER2-ultralow breast cancer cases.

An artificial intelligence technique for detecting DNA fragments shed by tumors and circulating in a patient's blood, developed by Johns Hopkins Kimmel Cancer Center investigators, could help clinicians more quickly identify and determine if pancreatic cancer therapies are working.

A deep learning model was able to predict future lung cancer risk from a single low-dose chest CT scan, according to new research published at the ATS 2025 International Conference.

WEDNESDAY, May 14, 2025 -- Artificial intelligence (AI) can help prevent breast cancers that develop between routine mammograms, by catching ones that trained radiologists would overlook, a new study says.Incorporating AI into mammography could...

Each year, millions of women undergo mammography to screen for breast cancer, yet tiny calcium specks—known as microcalcifications—often evade detection or are misread, leading to delayed diagnoses or unnecessary biopsies.

Weill Cornell Medicine's AI-based approach accurately groups cancer patients, improving treatment predictions and clinical trial participant selection.

A new AI tool, FaceAge, analyses selfies to estimate biological age, which, according to a recent study, is a stronger indicator of cancer survival than actual age.

Lung cancer is one of the most challenging diseases, making early diagnosis crucial for effective treatment.

This week, physicists at CERN reported the transmutation of lead into gold in the Large Hadron Collider, raising the possibility that a Science X alchemy vertical could be on the horizon. An international research collaborative developed a new method to identify bacteria within minutes. And researchers in California have identified tap water as another transmission pathway for E. coli bacteria.

Researchers developed FaceAge, an AI tool that calculate's a patient biological age from a photo of their face. In a new study, the researchers tied FaceAge results to health outcomes in people with cancer: When FaceAge estimated a younger age than a cancer patient's chronological age, the patient did significantly better after cancer treatment, whereas patients with older FaceAge estimates had worse survival outcomes.

A new AI model can deduce a person's biological age using a selfie. Could it be used to guide cancer treatment decisions?

With 98.4% accuracy in melanoma detection, SkinEHDLF demonstrates the potential of hybrid deep learning models in transforming dermatological diagnostics.

Eyes may be the window to the soul, but a person's biological age could be reflected in their facial characteristics. Investigators from Mass General Brigham developed a deep learning algorithm called FaceAge that uses a photo of a person's face to predict biological age and survival outcomes for patients with cancer.

A UCLA study reveals AI's potential to detect interval breast cancers earlier, improving screening protocols and patient outcomes in breast cancer treatment.

A new study suggests that artificial intelligence (AI) could help detect interval breast cancers before they become more advanced and harder to treat.

AI-derived predictive biomarker identifies two thirds of patients with high-risk prostate cancer who may benefit from extended hormone therapy.

An AI-assisted skin cancer detection tool has been given the green light by NICE whilst evidence is gathered on its effectiveness.

The Technical University of Munich's AI algorithm detects subtle kidney volume changes in cancer patients, predicting treatment-related kidney function decline.

A prospective trial established that 97% of patients were successfully discharged on the same day as receiving robotic partial nephrectomy.

MONDAY, April 28, 2025 -- A newly developed AI can predict which cancer patients are at risk for a life-threatening wasting syndrome, a new study says.The syndrome, called cachexia, accounts for about 20% of all cancer-related deaths, statistics...

An interdisciplinary research team has unveiled the world's first artificial intelligence (AI) model designed to classify both the cancer stage and risk category of thyroid cancer, achieving impressive accuracy exceeding 90%. This innovative AI model promises to significantly cut frontline clinicians' pre-consultation preparation time by approximately 50%, aligning with the HKSAR Government's initiative to harness AI technology in healthcare.

An AI-powered blood test for detecting 12 common cancers has been awarded government funding for further clinical trials.

GPs may soon be able to identify patients with an increased risk of lung cancer up to 4 months earlier than is currently the case.

The powerful potential of nanotechnologies and AI to detect oral cancer earlier and more accurately has been revealed by a University of Otago—Ōtākou Whakaihu Waka study published in ACS Nano.

Lung cancer screenings at Cincinnati Ohio's TriHealth are now more advanced and accurate thanks to ClearRead CT, a new AI-powered technology that will help identify potentially cancerous lung nodules in patients.

A new editorial was published in Oncotarget, Volume 16, on April 4, 2025, titled "Deep learning-based uncertainty quantification for quality assurance in hepatobiliary imaging-based techniques."

Deep Bio, a pioneer in AI-powered digital pathology, will present new research at the American Association for Cancer Research (AACR) Annual Meeting 2025, highlighting the role of artificial intelligence in enhancing biomarker quantification and cancer diagnostics.

An expert panel at ELCC 2025 reviews the MARIPOSA trial's implications for first-line therapy in EGFR-mutated NSCLC and broader advancements.

Leveraging the power of AI and machine learning technologies, researchers developed a more effective model for predicting how patients with muscle-invasive bladder cancer will respond to chemotherapy. The model harnesses whole-slide tumor imaging data and gene expression analyses in a way that outperforms previous models using a single data type.

Leveraging the power of AI and machine learning technologies, researchers at Weill Cornell Medicine developed a more effective model for predicting how patients with muscle-invasive bladder cancer will respond to chemotherapy.

Experts at the University of Leeds have created a penny-sized rolling robot that can non-invasively capture ultrasound scans of the gut to look for signs of cancer.

Lumea, a leader in digital pathology solutions. AIRA Matrix Private Limited, an innovative technology company for AI-based diagnostic, prognostic, and predictive applications in cancer care.