Negosentro.com | As of September 2016, Microsoft announced the launch of Project Hanover, including an exciting ensemble of initiatives focused on enhancing healthcare with artificial intelligence. Its researchers intend to “crack the cancer code” but deploying machine learning is never easy.
From testing computer simulations to seeing how cancer develops in the body, to applying Artificial Intelligence to radiology and creating biological cells that are programmable in ways similar to computers, numerous teams are on ambitious missions. Microsoft’s Project Hanover, NASA, Google’s DeepMind project in the UK, IBM, CRISPR and many other teams and technologies, are all aiming to improve health operations, treatments and diagnoses, globally. But what does this mean and what can we expect?
Project Hanover’s machine learning will review an immense amount of biomedical knowledge data from researchers, and then convert it into information scientists can use to help save lives. For example, hundreds of new cancer drugs are developed and thousands of new research articles are published every month. Doctors and medical professionals cannot possibly keep up-to-date on these developments, so machine learning helps by informing doctors of drug combinations and new developments in a concise, timely fashion.
Because cancer is not a single disease, but rather a thousand different diseases that share similar symptoms and growths, each cancer patient’s genes react differently to treatment. Precision medicine is a relatively new form of medical treatment still undergoing research in many areas, but Project Hanover wants to use AI to match treatments with individual patient genes and scientists believe it may be the key to unlocking the widespread use of precision medicine in the future.
Project Hanover also aims to use machine-learning and computer-vision systems to help radiologists understand how tumors grown within the body. Eventually, this understanding can help create biological cells that will fight cancerous growth. Overall, the project’s holistic mission is to improve the lives of those with chronic diseases and combat the soaring cost of healthcare spending in the United States.
Meanwhile, NASA is using space technology to fight cancer markers. The organization’s machine learning algorithm is used to identify similarities between galaxies and will now analyze tissue samples for signs of cancer. Those similarities could prove revolutionary for difficult to diagnose cancers like mesothelioma, pancreatic cancer, kidney or renal cell cancers and other neuroendocrine tumor (NET) cancers.
Google DeepMind project in the UK is improving radiotherapy scans to detect head and neck cancers. Complicated CT and MRI scans are currently used to detect and diagnose a variety of cancers. DeepMind applies a machine learning algorithm that automatically identifies cancerous and healthy cells and may be able to cut imaging read time by a few hours. When dealing with rare diseases and cancer patients that experience lengthy and invasive treatments and limited life expectancies, saving even a little bit of time allows doctors more time for patient care, education and research.
IBM Watson also uses machine learning to help oncologists develop treatment plans by interpreting a cancer patient’s clinical information, including physician notes, lab results and clinical research.
The list of technology related health advancement goes on:
- Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) is a naturally occurring, very precise genome editing tool made of DNA that is being used to diagnose and inactivate cancer mutations.
- Artificial Intelligence software interprets mammogram results 30 times faster than a human and with 99% accuracy.
- Nanorobotic agents have been created that can travel through a patient’s bloodstream to attack cancer cells in tumors with medication. So far the study has been performed on mice, but may be revolutionary when compared to modern day, invasive chemotherapy treatments.
- MR imaging, cobalt radiation delivery and intelligent software automation are being tested to provide high-quality pretreatment images, allowing physicians the ability to see soft tissue and adjust radiation doses in real-time while treatment is being delivered. This way, doctors can align treatment beams to exact cancer or tumor locations and avoid other sensitive internal organs.
- Gene editing technology is also being used to alter the DNA inside the immune system cells of mice, making them resistant to a tumor cell’s ability to switch them off. If research is successful in human trials, it could be another way for doctors to use a patient’s own immune system to fight disease.
Health care has always relied on technology. We’ve come a long way since the scalpels and hand tools of the 19th century and although we have a ways to go before curing cancer, we are moving closer and closer each day.