Researchers have shown that federated learning is successful in the context of brain imaging, by being able to analyze MRI scans of brain tumor patients and distinguish healthy brain tissue from cancerous regions.
Researchers have developed an AI algorithm that uses computer vision to analyze tissue samples from cancer patients.
Researchers have developed a new, faster method to identify cancer stem-like cells (CSCs), which could help improve the effectiveness of cancer treatments.
A new AI approach classifies a common type of brain tumour into low or high grades with almost 98% accuracy, researchers report.
Computer scientists working with pathologists have trained an AI tool to determine which patients with lung cancer have a higher risk of their disease coming back after treatment.
Pathologists who examined the computationally stained images could not tell them apart from traditionally stained slides.
Brain cancer patients in the coming years may not need to go under the knife to help doctors determine the best treatment for their tumors.
Researchers have developed a new approach to early diagnosis of lung cancer: a urine test that can detect the presence of proteins linked to the disease.
Researchers demonstrated a methodology that combines the bioprinting and imaging of glioblastoma cells in a way that more closely models what happens inside the human body.
Using a robot to treat brain aneurysms is feasible and could allow for improved precision when placing stents, coils and other devices.
Researchers have developed a tumor biosensing chip that can help determine the optimum dosage of chemotherapy required for a cancer patient.
Researcher have developed a computer method that uses MRI and machine learning to rapidly forecast genetic mutations in glioma tumors,
Researchers have developed a 'tumor-on-a-chip' that can better mimic the environment inside the body, paving the way for improved screening of potential cancer fighting drugs.
A novel method of combining advanced optical imaging with an artificial intelligence algorithm produces accurate, real-time intraoperative diagnosis of brain tumors.
Researchers have developed a new algorithm that enables automated detection of metastases at the level of single disseminated cancer cells in whole mice.
A software tool uses artificial intelligence to recognize cancer cells from digital pathology images — giving clinicians a powerful way of predicting patient outcomes.
An AI platform can analyze genomic data extremely quickly, picking out key patterns to classify different types of colorectal tumors and improve the drug discovery process.
Scientists can determine which lung-cancer patients will benefit from expensive immunotherapy.
A 3D-printed cell trap developed in the laboratory at Georgia Tech captures blood cells to isolate tumor cells from a blood sample.
Researchers found that using 3D models to prepare for kidney tumor surgeries resulted in substantial improvements, including shorter operating times.
Researchers used artificial intelligence to develop a new classification method which identifies the primary origins of cancerous tissue based on chemical DNA changes.
Researchers are developing microrobots that can deliver drugs to specific spots inside the body while being monitored and controlled from outside the body.
Stomach and colorectal cancer: Identifying patients at an early stage who are suitable for artificial intelligence immunotherapy.
Researchers have built a set of magnetic ‘tweezers’ that can position a nano-scale bead inside a human cell in three dimensions with unprecedented precision.
Researchers have created new machine learning software that can forecast the survival rates and response to treatments of patients with ovarian cancer.
Thanks to developments in 3D bioprinting, the UT researchers could create a miniature brain model representing the delicate tissue around the tumor, including the macrophages.
Researchers have developed a technique with which bone implants that are precisely fitting, stable and variable in dimensions can be 3D printed from a special plastic.
In the age of big data, cancer researchers are discovering new ways to monitor the effectiveness of immunotherapy treatments.
Robotic approach assists with a three-part, two-day complex procedure for rare tumor removal.
