Cancer researchers are using new technological tools to find better ways to diagnose and treat the killing disease. Many innovative measures are undertaken to fight off cancer. In fact, based on a weed vape guide at ventsmagazine, studies have found that even marijuana oil can be applied for cancer treatment. But for the most part, new advances in cancer diagnosis and therapy leverage have improved to help detect and beat the disease. Posted below are some of the technological innovations that made it possible to fight cancer.
Maximizing and Atomizing Research
Microsoft’s Project Hanover was developed for maximizing research. It aims to use machine learning and natural language processing to help doctors sift through many medical studies published each year. That way, they can better decide which cancer treatments are most effective and personalized for each patient.
The system automatically searches all published research studies to find the most relevant information about a particular patient. Finally, to help doctors design the most effective cancer treatments, the team will rely on a Microsoft Azure cloud computing platform. Microsoft is also working with the Knight Cancer Institute at Oregon Health & Science University to develop a machine learning approach to personalize treatments for acute lymphoblastic leukemia, a rare and often fatal cancer.
Enhancing Cancer Markers
NASA uses space technology to detect cancer markers. The institution’s machine learning algorithm that detects similarities between galaxies will now examine tissue samples for signs and symptoms of cancer. NASA’s Jet Propulsion Laboratory renewed a partnership to collect biomarker research into a searchable network. Doctors can then compare a CT scan, for example, with an archive of similar images to look for early signs of cancer-based on a patient’s demographics. This could lead to new techniques for early detection of cancer risk assessment.
Improving Radiotherapy Scans
DeepMind Health, part of Google, has been working on radiotherapy scans to improve head and neck cancer detection. This complicated scan takes doctors about four hours. It creates a detailed map of which areas should be treated with radiation therapy and avoided. DeepMind uses machine learning to help doctors with this process.
It has an algorithm that automatically determines the difference between healthy and cancerous cells. This could reduce the time it takes to read a tumor to one hour. This allows doctors more time for patient care, education, research, and other activities.
Analyzing Research and Developing Treatment
IBM Watson uses machine learning to help oncologists analyze research and develop treatment plans. Since 2014, analysts and clinicians at Memorial Sloan Kettering Cancer Center have worked with Watson to interpret patients’ clinical information and find personalized, evidence-based treatment options. This involves interpreting doctor’s notes, lab results and the latest clinical research. Oncologists can use Watson from anywhere to help them make more informed decisions and act more quickly, the hospital said. Watson can help physicians better qualify patients for clinical trials. The system can be accessed from a tablet and is already used at hospitals in India, Thailand, and other countries.
Inactivating Cancer Mutations
In a study published in the Journal of the National Cancer Institute, CRISPR technology was used to identify and activate cancer-causing mutations. CRISPR (clustered regularly interspaced short palindromic repeats) is an exact and natural tool used to inactivate cancer mutations. There are currently more than 500,000 mutations in cancer.
Researchers from the National Center for Tumor Disease Dresden and the German Consortium for Translational Cancer Research found that over 80% of these mutations can be targeted with the CRISPR technology without harming healthy tissues.…