To better leverage cancer data for research, scientists are developing an artificial intelligence-based natural language processing tool to improve information extraction from textual pathology reports.
By adding infrared capability to the ubiquitous, standard optical microscope, researchers hope to bring cancer diagnosis into the digital era.
Usind deep learning and digital scanning of conventional hematoxylin and eosin-stained tumor tissue sections, researchers have developed a clinically useful prognostic marker.
Researchers have developed a tumor biosensing chip that can help determine the optimum dosage of chemotherapy required for a cancer patient.
Researchers have developed a method based on artificial intelligence for histopathological diagnosis and grading of prostate cancer.
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.
Using a computer algorithm, scientists at Uppsala University have identified a promising new treatment for neuroblastoma.
Artificial intelligence can detect one of the most common forms of blood cancer—acute myeloid leukemia (AML)—with high reliability.
An AI has successfully found features in pathology images from human cancer patients, without annotation, that could be understood by human doctors.
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.
Researchers have used a chip-based sensor with an integrated laser to detect very low levels of a cancer protein biomarker in a urine sample.
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.
Researchers refined application of terahertz radiation to promote the analysis of multi-layered tissues for medical purposes and be used for wound treatment.
Radiologists assisted by deep learning based software were better able to detect malignant lung cancers on chest X-rays.
Using machine learning, researchers have built a tool that detects genetic mutations that trigger the immune system, helping identify which cancer patients are likely to benefit from 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 from Johns Hopkins Medicine show that wearable activity trackers are a reliable tool for predicting death risk in older adults.
Researchers from Thomas Jefferson University use machine learning on ultrasound images of thyroid nodules to predict risk of malignancy.
Scientists have now developed guidelines that should enable the safe development of nanoparticles for medical use.
Researchers used artificial intelligence to develop a new classification method which identifies the primary origins of cancerous tissue based on chemical DNA changes.
Spectroplast has developed a method to make silicone products such as hearing aids, breast prosthesis for breast cancer patients using a 3D printer.
Advanced computer models of diseases can be used to improve diagnosis and treatment. The goal is to develop the models to “digital twins” of individual patients.
Collaborators are developing an endoscopic robotic system with two-handed dexterity at a much smaller scale than existing options.
Revolutionary material could lead to 3D-printable magnetic liquid devices for the fabrication of artificial cells that deliver targeted drug therapies to diseased cells.
Using AI and biosensors, researchers have created a device that can determine whether targeted chemotherapy drugs are working on individual cancer patients.
Scientists have developed a robot that looks and moves like a jellyfish; the aim is for Jellyfishbot to be applied in the treatment of cancer.
Stomach and colorectal cancer: Identifying patients at an early stage who are suitable for artificial intelligence immunotherapy.
Researchers have utilized machine learning capabilities to assist with the challenging task of grading tumor patterns and subtypes of lung adenocarcinoma.
Scientists are using 3D technology to help rebuild the faces of cancer patients, those hurt in accidents and people born with complex facial deformities.
A new ultrasensitive diagnostic device could allow doctors to detect cancer quickly from a droplet of blood or plasma, leading to timelier interventions and better outcomes for patients.
Several research groups at the Berlin Institute of Health (BIH) are working on digitally combating cancer, comparing experiences with different diagnostic and treatment methods.
Doctors could get a head start treating cancer thanks to new AI developed at the University of Surrey that is able to predict symptoms and their severity throughout the course of a patient’s treatment.
UT Southwestern has become the first medical center in Texas to use a robotic tool that allows surgeons to perform complicated operations using just a single incision.
Medical software that overlays tumour information from MRI scans onto ultrasound images can help guide surgeons conducting biopsies and improve prostate cancer detection.
