Russia’s ongoing nuclear fallout challenges.
MUSLYUMOVO, Russia (AP) — At first glance, Gilani Dambaev looks like a healthy 60-year-old man and the river flowing past his rural family home appears pristine. But Dambaev is riddled with diseases that his doctors link to a lifetime’s exposure to excessive radiation, and the Geiger counter beeps loudly as a reporter strolls down to the muddy riverbank.
Some 50 kilometers (30 miles) upstream from Dambaev’s crumbling village lies Mayak, a nuclear complex that has been responsible for at least two of the country’s biggest radioactive accidents. Worse, environmentalists say, is the facility’s decades-old record of using the Arctic-bound waters of the Techa River to dump waste from reprocessing spent nuclear fuel, hundreds of tons of which is imported annually from neighboring nations.
The results can be felt in every aching household along the Techa, where doctors record rates of chromosomal abnormalities, birth defects and cancers vastly higher than the Russian average — and citizens such as Dambaev are left to rue the government’s failure over four decades to admit the danger.
Nice; however, I see also 3D printing along with machine learning being part of any cosmetic procedures and surgeries.
With an ever-increasing volume of electronic data being collected by the healthcare system, researchers are exploring the use of machine learning—a subfield of artificial intelligence—to improve medical care and patient outcomes. An overview of machine learning and some of the ways it could contribute to advancements in plastic surgery are presented in a special topic article in the May issue of Plastic and Reconstructive Surgery®, the official medical journal of the American Society of Plastic Surgeons (ASPS).
“Machine learning has the potential to become a powerful tool in plastic surgery, allowing surgeons to harness complex clinical data to help guide key clinical decision-making,” write Dr. Jonathan Kanevsky of McGill University, Montreal, and colleagues. They highlight some key areas in which machine learning and “Big Data” could contribute to progress in plastic and reconstructive surgery.
Machine Learning Shows Promise in Plastic Surgery Research and Practice
Machine learning analyzes historical data to develop algorithms capable of knowledge acquisition. Dr. Kanevsky and coauthors write, “Machine learning has already been applied, with great success, to process large amounts of complex data in medicine and surgery.” Projects with healthcare applications include the IBM Watson Health cognitive computing system and the American College of Surgeons’ National Surgical Quality Improvement Program.
Lookout Silicon Valley — FDA is here. I do suggest tech companies working on technologies that enhances or alters any bio living things to ensure that your certifications, processes are well defined and govern, and in some cases the engineers, etc. will need some level of a medical background and certifications as well. Why many have stated that future engineers and technologists will need a bio background through education, etc.
Helmy Eltoukhy’s company is on a roll. The start-up is a leading contender in the crowded field of firms working on “liquid biopsy” tests that aim to be able to tell in a single blood draw whether a person has cancer.
Venture investors are backing Guardant Health to the tune of nearly $200 million. Leading medical centers are testing its technology. And earlier this month, it presented promising data on how well its screening tool, which works by scanning for tiny DNA fragments shed by dying tumor cells, worked on an initial group of 10,000 patients with late-stage cancers.
Just one thing is holding the company back: Guardant Health has yet to get approval from Food and Drug Administration.
A genetic therapy has improved the vision of patients who would otherwise have gone blind.
A clinical study by British scientists has shown that the improvement is long-lasting and so the therapy is suitable to be offered as a treatment.
The researchers will apply for approval to begin trials to treat more common forms of blindness next year.
