With the advent of pharmacogenomics, machine learning research is well underway to predict patients' drug response that varies by individual from the algorithms derived from previously collected data on drug responses.
Researchers have found a way to send tiny, soft robots into humans, potentially opening the door for less invasive surgeries and ways to deliver treatments for several conditions.
Researchers have developed an robotic system to enhance the safety and efficacy of endoscopic submucosal dissection (ESD) for the treatment of gastrointestinal cancer.
The new 3D hydrogels provide high rates of cell proliferation, as they mimic lymph nodes, where T-cells reproduce in vivo.
Scientists have paired 3D-printed, living human brain vasculature with advanced computational flow simulations to better understand tumor cell attachment to blood vessels.
Robotic surgery for patients with early stage, oropharyngeal squamous cell cancer is associated with improved health outcomes, including better long-term survival.
Nanoengineers plan to develop an immunotherapy for ovarian cancer using 3D-bioprinted plant virus nanoparticles.
An anaesthesia team used 3D printing and virtual reality to produce an exact model of the airway of a 7-year-old girl in order to prepare properly for an operation to remove part of her lung.
EPFL students teamed up with startup IcosaMed to develop the SmartBra – the first piece of smart clothing that can be used for cancer prevention.
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.
Thanks to smart software doctors will soon be able to detect early signs of esophageal cancer in patients with so-called Barrett’s esophagus.
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.