Related Providers need to understand their patients better, panelists say New report examines how AI might affect urban life The problems with LGBTQ health care What artificial intelligence will look like in 2030 In 2016, a Google team announced it had used artificial intelligence to diagnose diabetic retinopathy — one of the fastest-growing causes of blindness — as well as trained eye doctors could.In December 2018, Microsoft and the pharmaceutical giant Novartis announced a partnership to develop an AI-powered digital health tool to be deployed against one of humanity’s oldest scourges — leprosy, which still afflicts 200,000 new patients annually.Around the world, artificial intelligence is being touted as the next big thing in health care, and a potential game-changer for billions living in regions where medical infrastructure is inadequate and doctors and nurses scarce.Despite that potential, some fear that too-rosy views of AI’s promise will lead to disappointment and, worse, rob scarce health care dollars from desperately needed investments in existing medical infrastructure. Experts in AI and global health gathered at Harvard this week to survey the complex artificial intelligence-global health landscape, examine what’s being done today and what’s promised for tomorrow, and try to separate reality from fantasy when it comes to AI’s potential impact on global health.“The promise of AI is enormous, but the challenges are often glossed over,” said Ashish Jha, faculty director of Harvard Global Health Institute (HGHI). “We have this sense that they’ll somehow take care of themselves. And we know they will not.”About 50 experts in the use of artificial intelligence and other digital health care technologies gathered at Loeb House for an all-day symposium on “Hype vs. Reality: The Role of AI in Global Health,” sponsored by HGHI. It featured talks by representatives from academia, health care, and industry, including Google AI and the pharmaceutical giant Novartis. Principals also spoke for startups Aindra Systems, which uses AI to rapidly analyze pap smears for evidence of cervical cancer, and Ubenwa, which has developed an AI-based system to analyze infant cries to detect birth asphyxia, a leading killer of children under 5 that’s traditionally diagnosed through time-consuming blood tests and lab analyses.Despite the symposium’s cautionary tone, several speakers described AI’s potentially far-reaching effects on global health. Image analysis, a key aspect of disease screening and diagnosis, is an area ripe for rapid change. Lily Peng, product manager for Google AI, described Google’s work on diabetic retinopathy. The company’s researchers used a “deep learning” algorithm that reviewed thousands of images of both normal and damaged eyes and developed a screening tool for the condition — a side effect of poorly controlled diabetes — that performed as well as trained ophthalmologists.That tool, and similar ones for other conditions, can provide valuable screening and referral services in rural areas that have little medical infrastructure. Their promise is of a future where initial screening can be guided by community health workers — far more numerous than trained physicians — who can then refer those who test positive to clinics and hospitals staffed with better-trained medical personnel.But the question remained: How effectively would such interventions perform in the field? During a Q&A session, one participant described a device developed by an engineer in Cameroon to diagnose cardiac problems in remote areas. The device was designed to be used by rural nurses who could send results to city-based cardiologists for review. Problems occurred, however, because the nurses entered data in the wrong fields, spotty internet connections made it hard to transmit the data, and finally, when the information made it to the city, the cardiologists were often too busy to examine it.Adam Landman, chief information officer at Brigham and Women’s Hospital and an associate professor of emergency medicine at Harvard Medical School, said it’s important that AI not be viewed as a solution in search of a problem, but that the health care outcomes be considered first and AI considered as one tool among others to address it.“The key with any technology — and AI is just one of them — is it needs to actually solve a health care [problem],” Landman said. “The need [should] drive the use of it and not the technology drive the use. They may not need AI to start. In fact, they may not need any technology to start. They may need more people, more health care workers. There may be other things to invest in before technology, or technology may be part of that solution.”,Ann Aerts, head of Novartis Foundation, said severe shortages of doctors and nurses in some parts of the world demand innovative approaches to health care. Technology has already transformed the way medicine is practiced in some resource-poor settings. In Ghana, a telehealth pilot has evolved into a national telehealth program that keeps a center staffed 24 hours a day, seven days a week, with doctors, nurses, and health workers. The program isn’t a substitute for skilled medical care, but Aerts said that about 70 percent of all health care problems can be solved over the phone. The program highlights how innovative solutions can be found to the health care shortage that is a fact of life in many parts of the world.“This calls for innovating the way we deliver health services, for transforming our health systems,” Aerts said. “We cannot go back to the old model. It doesn’t work. … Let’s look at how we can reimagine the way we deliver health services.”John Halamka, chief information officer at Beth Israel Deaconess Medical Center and the International Healthcare Innovation Professor of Emergency Medicine at Harvard Medical School, said that AI has the potential not only to meet needs where care is scarce, but also to improve care and reduce errors where doctors and nurses are present. He told of a woman who visited a doctor in northern India because of abdominal pain. She was incorrectly diagnosed and paid for repeated testing and physician visits. Ultimately, she was forced her to sell her house and cow, impoverishing her family.She was finally diagnosed correctly with abdominal tuberculosis, a condition that might rarely be seen in the U.S., but ought to have been considered much sooner in India, which has 1.3 million active cases of tuberculosis, Halamka said.Halamka consulted on another case, in Bakersfield, California, that shows the problem is not restricted to the developing world. A young woman was arrested for running naked through a Walmart parking lot at 3 a.m. When Halamka called to talk to the emergency room physician, he was told that the young woman’s urine had tested positive for cannabis, so he had discharged her.“And of course all of us in this room know that cannabis consumption results in young women running naked through parking lots at 3 in the morning — never,” Halamka said. “We flew her to Logan [International Airport], brought her to Beth Israel Deaconess … [and she had] the worst case of meningitis any of us had ever seen. Again thinking back on AI, if we had [it trained by the experiences of] a million young women with altered mental status, how many would include cannabis as the primary cause? Probably, again, none. But in a person who lives with a lot of other 20-year-olds who have lots of infectious diseases, what are the chances of meningitis? Actually, pretty significant.”Halamka said that artificial intelligence and machine learning has progressed rapidly since the late 1990s, when it took six months of work to get AI to recognize a giraffe as a mammal. Today, he said, designing an AI algorithm itself is relatively easy, but algorithms have to be trained on large amounts of data from past cases, and it can be challenging to ensure that data is available, appropriate, and unbiased.“Gathering and curating good-quality data, unbiased data, and using it to train these algorithms is still a challenge,” Halamka said. “The quality of our data is poor. We get social security numbers wrong 11 percent of the time. We even get gender wrong 3 percent of the time. Men have babies, women have prostatectomies. We need to work on curated data sets if we’re going to be successful with AI.”Designers of AI health care applications, Aerts and other speakers said, should also guard against AI becoming a benefit solely for the rich, a factor that increases inequality instead of helping close the gap between haves and have-nots. Ashley Nunes, a fellow at Harvard Law School, said there’s a perception that AI will cut health care costs, making it more affordable for the poor, but there’s no guarantee that will happen.Nunes pointed to self-driving cars, which are projected to make roads safer. Accident data show the poor suffer the most physical and economic harm from road accidents, so hypothetically they could see the most benefit. But the added cost of the driverless technology means it will likely disproportionately benefit wealthier drivers, highlighting how important it is to ensure that tech solutions in health care benefit everyone.Jha said he looks forward to a time when AI is just another tool in the health care toolbox.“The whole idea of digital health reminds me that about 20 years ago we used to talk about e-commerce,” he said. “We don’t talk about e-commerce anymore; we just talk about commerce.”
If your drive for spring cleaning demands a clean house inside and out, you may wonderwhat to do with those dirty shingles.Before you pay high costs to replace your roof, try cleaning it.In high-humidity areas, roofs often turn dark brown or black within five to seven yearsbecause fungi and algae feed on dirt in shingles.The fungus can start growing on a new roof right after the first shingle is laid down,says Dale Dorman, a housing specialist with the University of Georgia Extension Service.”The growth first appears as black streaks or wedge-shaped areas that spreadacross the roof,”> Dorman says. “After a few years, the discolored areasmerge, and uniform discoloration eventually results.”Fungus and algae growth is usually heaviest on west- or north-facing roofs or onthose shaded by trees,” she says. “Dew dries more slowly in these areas.”The good news is that these stains don’t mar the roof’s strength or service life.Research at Mississippi State University found several chemicals can remove shinglediscoloration caused by fungi, algae and lichen.”One of the best cleaners is liquid household bleach,” Dorman says. “Andit doesn’t damage the shingles.”Apply a 75 percent solution of household bleach (three parts bleach to one part water)to asphalt shingles. Use one gallon of solution per 30 to 50 square feet of roof surface.About 15 gallons of bleach will treat 1,000 square feet of roofing. “Roofs will remain clean for at least five years if sprayed with the 75 percentbleach solution,” Dorman says.Cleaning power decreases with less bleach. A 10 percent bleach solution will kill thefungus, but it won’t clean the roof immediately. The dead organisms will eventually washaway with rain. But the roof will remain clean for only about a year.Clean your roof in strips starting at the peak and working toward the eaves, Dormansays.”Treated roofs are slippery when wet, so work from a ladder,” she says.”Use a clean garden sprayer to apply the mixture.”Avoid skin contact with the solution,” she says, “and cover any shrubsor plants below the eaves with plastic. Dilute any solution reaching the ground byspraying it with water.If you have rain gutters at the eaves, remove all leaf screening and place a gardenhose in the gutter. This will dilute the solution as it drips from the roof. You don’tneed to scrub the roof or rinse off the solution.”While cleaning the shingles, look for damage on your roof,” Dorman says.”Note cracks in the shingle surface, curling corners, buckling front edges or loss ofgranules.””If you have to reroof, use a fungus-resistant shingle that carries a 20-yearlimited warranty against fungus growth,” she says. “The shingles release zincgranules when it rains, destroying fungus and algae.”The fungus-resistant shingles offer an inexpensive way to maintain beauty, Dorman says.
BLOG: 2016-2017 Budget Must Close Deficit to Avert Funding Crisis By: Jeff Sheridan, Press Secretary June 22, 2016 Like Governor Tom Wolf on Facebook: Facebook.com/GovernorWolf Budget News, The Blog It is a widely-acknowledged fact that a reliance on one-time fixes and delayed payments has led Pennsylvania into a dire financial crisis: a massive deficit that threatens our investment in schools, social programs and public safety.Governor Wolf is working with Republicans and Democrats in the General Assembly and he’s engaged them for their ideas to accomplish this task responsibly.While some may differ on the extent of the problem, nearly every budget analyst believes our deficit for the 2016-2017 budget is well over one billion dollars.Pennsylvania’s choice is to face this head-on and find revenue and savings to balance the budget honestly with sustainable revenue and end our reliance on gimmicks, or we must prepare to face another round of major cuts to important programs.Governor Wolf and Republicans and Democrats who’ve acknowledged our budget crisis are not alone – credit rating agencies continue to call for action on the deficit.In March, Standard and Poor’s said: “In our view, the immediate credit concern is that failure to act in the current fiscal year could compound future fiscal gaps.” Moody’s, Fitch and PNC have all repeatedly issued the same warnings.No one party or moment in time is solely responsible for the crisis we now face – but the responsibility falls on all leaders now to fix it.As the budget deadline nears, we need to end our reliance on one time fixes and delayed payments that have patched our budgets in the past. We need a truly balanced budget with sustainable revenue.Governor Wolf has compromised on taxes, liquor reform, and pension reform, but he will not compromise on the mathematical reality of Pennsylvania’s financial situation. SHARE Email Facebook Twitter