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Creating Smart Home Ecosystems — Enabling Health & Well-Being In Every Home — Viren Shah, VP & Chief Digital Officer, GE Appliances, Haier

Mr. Viren Shah is Vice President & Chief Digital Officer, at GE Appliances (GEA — https://www.geappliances.com/), the American home appliance manufacturer, now a majority owned subsidiary of the Chinese multinational home appliances company, Haier (https://www.haierappliances.com/).

Mr. Shah has been with GEA since October 2,018 in which time he was appointed to lead the business through a digital transformation with a focus on data/intelligence at the center of gravity.

Prior to becoming part of the Haier company, Mr. Shah was the CIO at Masco Cabinetry, and CIO Council Leader for their parent company, Masco Corporation, the international conglomerate manufacturer of products for the home improvement and new home construction markets.

Mr. Shah has more than 20 years of global experience in creating business value using technology with a strong focus on customers for Fortune 10 organizations, such as his decade at the Walmart organization. He has contributed as a senior leader towards the success of startups, turnarounds and global mergers and acquisitions.

Mr. Shah implemented “Think Global and Act Local” methodologies, utilizing operational and cultural experience in areas of IT strategy, omnichannel, business development and governance in more than 20 countries across the Americas, Australia, Europe, Asia and Africa.

Mr. Shah holds a bachelor’s degree in computer science from Bombay University, a master of business administration degree in international marketing/short-term finance from the New York Institute of Technology, and an executive education certificate in digital marketing strategies for digital economy from the Wharton School.

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As the medical community’s understanding of the application of augmented intelligence (AI) in health care grows, there remains the question of how AI—often called artificial intelligence—should be incorporated into physician training. The term augmented intelligence is preferred because it recognizes the enhancement, rather than replacement, of human capabilities.

Understanding how AI can affect patients may help learners appreciate its relevance, he noted, adding that the National Board of Medical Examiners exam now tests physicians-in-training on health systems science, and there are questions about health care AI specifically.

But AI doesn’t just relate to systems issues. It also has a home within evidence-based medicine (EBM).

Full Story:

“Understandably, there have also been many who have been concerned about fitting new content into already overcrowded curricula,” Dr. James said. This can include figuring out who on the faculty will take on teaching new content.

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A slew of new studies now shows that the area of the brain responsible for initiating this action — the primary motor cortex, which controls movement — has as many as 116 different types of cells that work together to make this happen.

The 17 studies, appearing online Oct. 6 in the journal Nature, are the result of five years of work by a huge consortium of researchers supported by the National Institutes of Health’s Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) Initiative to identify the myriad of different cell types in one portion of the brain. It is the first step in a long-term project to generate an atlas of the entire brain to help understand how the neural networks in our head control our body and mind and how they are disrupted in cases of mental and physical problems.

“If you think of the brain as an extremely complex machine, how could we understand it without first breaking it down and knowing the parts?” asked cellular neuroscientist Helen Bateup, a University of California, Berkeley, associate professor of molecular and cell biology and co-author of the flagship paper that synthesizes the results of the other papers. “The first page of any manual of how the brain works should read: Here are all the cellular components, this is how many of them there are, here is where they are located and who they connect to.”

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Despite high vaccine coverage and effectiveness, the incidence of symptomatic infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been increasing in Israel. Whether the increasing incidence of infection is due to waning immunity after the receipt of two doses of the BNT162b2 vaccine is unclear.

As the rollout of vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)1,2 is expanding worldwide, data on the durability of protection are limited. A randomized, controlled trial and real-world studies have shown vaccine efficacy of 94 to 95% with the BNT162b2 vaccine (Pfizer–BioNTech) and vaccine effectiveness in preventing symptomatic coronavirus disease 2019 (Covid-19) 7 days or more after receipt of the second dose of vaccine.1,3–5 Real-world effectiveness and immunogenicity data describing the antibody kinetics over time after vaccination are beginning to appear, but a complete picture of the duration of immunity is not yet available. We recently reported that breakthrough infection in BNT162b2-vaccinated persons was correlated with neutralizing antibody titers.6 However, a threshold titer that can predict breakthrough infection has not been defined.

The BNT162b2 vaccine elicits high IgG and neutralizing antibody responses 7 to 14 days after receipt of the second dose. Lower antibody levels have been shown to develop in older persons, men, and persons with an immunosuppressed condition, which suggests that antibody titers in these populations may decrease earlier than in other populations.7,8 A decrease in anti-spike (S) antibody levels by a factor of two was observed from the peak (at 21 to 40 days) to 84 days after receipt of the second dose of the BNT162b2 vaccine among 197 vaccinated persons.9 Here, we report the results of a large-scale, real-world, longitudinal study involving health care workers that was conducted to assess the kinetics of immune response among persons with different demographic characteristics and coexisting conditions throughout the 6-month period after receipt of the second dose of the BNT162b2 vaccine.

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A FIVE-DAY COURSE of molnupiravir, the new medicine being hailed as a “huge advance” in the treatment of Covid-19, costs $17.74 to produce, according to a report (pdf) issued last week by drug pricing experts at the Harvard School of Public Health and King’s College Hospital in London. Merck is charging the U.S. government $712 for the same amount of medicine, or 40 times the price. (taxpayer funded mind you)

The Covid-19 treatment molnupiravir was developed using funding from the National Institutes of Health and the Department of Defense.

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It probably didn’t feel like much, but that simple kind of motion required the concerted effort of millions of different neurons in several regions of your brain, followed by signals sent at 200 mph from your brain to your spinal cord and then to the muscles that contracted to move your arm.

At the cellular level, that quick motion is a highly complicated process and, like most things that involve the human brain, scientists don’t fully understand how it all comes together.

Now, for the first time, the neurons and other cells involved in a region of the human, mouse and monkey brains that controls movement have been mapped in exquisite detail. Its creators, a large consortium of neuroscientists brought together by the National Institutes of Health’s Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative, say this brain atlas will pave the way for mapping the entire mammalian brain as well as better understanding mysterious brain diseases — including those that attack the neurons that control movement, like amyotrophic lateral sclerosis, or ALS.

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There’s a lot of excitement at the intersection of artificial intelligence and health care. AI has already been used to improve disease treatment and detection, discover promising new drugs, identify links between genes and diseases, and more.

By analyzing large datasets and finding patterns, virtually any new algorithm has the potential to help patients — AI researchers just need access to the right data to train and test those algorithms. Hospitals, understandably, are hesitant to share sensitive patient information with research teams. When they do share data, it’s difficult to verify that researchers are only using the data they need and deleting it after they’re done.

Secure AI Labs (SAIL) is addressing those problems with a technology that lets AI algorithms run on encrypted datasets that never leave the data owner’s system. Health care organizations can control how their datasets are used, while researchers can protect the confidentiality of their models and search queries. Neither party needs to see the data or the model to collaborate.

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With almost instant improvement.

A team of researchers from the University of California, San Francisco Health has successfully treated a patient with severe depression by targeting the specific brain circuit involved in depressive brain patterns and resetting them thanks to a new proof-of-concept intervention.

Even though it centers around one patient, the groundbreaking study, which has now been published in Nature Medicine, is an important step toward bringing neuroscience advances and the treatment of psychiatric disorders, potentially helping millions of people who suffer from depression.

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Based on Transformers, our new architecture advances genetic research by improving the ability to predict how DNA sequence influences gene expression.

When the Human Genome Project succeeded in mapping the DNA sequence of the human genome, the international research community were excited by the opportunity to better understand the genetic instructions that influence human health and development. DNA carries the genetic information that determines everything from eye colour to susceptibility to certain diseases and disorders. The roughly 20,000 sections of DNA in the human body known as genes contain instructions about the amino acid sequence of proteins, which perform numerous essential functions in our cells. Yet these genes make up less than 2% of the genome. The remaining base pairs — which account for 98% of the 3 billion “letters” in the genome — are called “non-coding” and contain less well-understood instructions about when and where genes should be produced or expressed in the human body.

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