Therapeutic Area


An AI Epidemiologist Sent the First Warnings of the Wuhan Virus

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On January 9, the World Health Organization notified the public of a flu-like outbreak in China: a cluster of pneumonia cases had been reported in Wuhan, possibly from vendors' exposure to live animals at the Huanan Seafood Market. The US Centers for Disease Control and Prevention had gotten the word out a few days earlier, on January 6. But a Canadian health monitoring platform had beaten them both to the punch, sending word of the outbreak to its customers on December 31. BlueDot uses an AI-driven algorithm that scours foreign-language news reports, animal and plant disease networks, and official proclamations to give its clients advance warning to avoid danger zones like Wuhan. Speed matters during an outbreak, and tight-lipped Chinese officials do not have a good track record of sharing information about diseases, air pollution, or natural disasters.


How artificial intelligence provided early warnings of the Wuhan virus

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During the kind of virus outbreak that China and other nations are now contending with, time is of the essence. Such was the case in 2002 and 2003, when Chinese authorities were accused of covering up the SARS epidemic that eventually claimed over 740 lives around the world. With the current outbreak, involving a coronavirus that originated in Wuhan and has so far taken over 40 lives, the Chinese government is being more transparent, as Germany's health minister noted to Bloomberg yesterday on the sidelines of the World Economic Forum in Davos.


Brain tech is coming of age, but will it make you smarter?

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With Brain Computer Interface (BCI), scientists and medical practitioners are already helping people with damaged limbs, eyes or ears regain sensations like touch, grasp, eyesight and hearing, by recording specific brain signals and translating them into actions. BCI exists in two forms: the first is the non-invasive, which includes devices or electrodes that are worn on the body. The second is the invasive variant where an electrode is implanted under the scalp so it can record information directly from the neurons in the brain. "The moment you talk about the invasive variety, it opens up a lot of possibilities. We have always had cochlear implants for cornea and ear, and pacemakers for heart. They have been fairly successful. Invasive variety can never be a mass product as it has to be entered carefully in a sophisticated medical environment only," points out Kumaar Bagrodia, founder and chief executive officer of NeuroLeap, a neuroscience startup.


Alexa learns to give useful advice to blind people

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Amazon and the UK's Royal National Institute of Blind People (RNIB) have worked together to make Alexa more useful to those suffering from visual impairment conditions. Thanks to this collaboration, the AI-powered personal assistant can offer advice on living with sight loss, obtained directly from RNIB's Sight Loss Advice Service. "Voice assistant technology is playing an ever-increasing role in transforming the lives of blind and partially sighted people," said David Clarke, director of services at RNIB. "Voice assistants can enable independence, helping to break down accessibility barriers to a more inclusive society. By using this technology to increase the reach of our own resources, we are ensuring that people can immediately get essential information about sight conditions, their rights, and the support available, simply by asking out loud." RNIB is a charity established in 1868, originally to provide better quality literature for the blind. Today, it offers information, support and advice to almost two million people in the UK, under the patronage of the Queen.


Developments in Artificial Intelligence for Mental Health Care

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Advances in artificial intelligence have considered computers to help doctors in diagnosing disease and help screen patients' vital signs from any area. Significant advances have been made in artificial intelligence that will soon affect the manner in which mental health care is practiced in everyday clinical settings. The outcome will be increasingly individualized treatment integrating both traditional and evidence-based complementary and alternative medicine (CAM) modalities, progressively viable and more cost-effective medicines of numerous mental health issues, and improved results. In Europe, the WHO assessed that 44.3 million individuals suffer from depression and 37.3 million endure with anxiety. Diagnosis of mental health disorders depend on an age-old method that can be subjective and unreliable, says paper co-creator Brita Elvevåg, a cognitive neuroscientist at the University of Tromsø, Norway.


How artificial intelligence provided early warnings of the Wuhan virus

#artificialintelligence

During the kind of virus outbreak that China and other nations are now contending with, time is of the essence. The earlier the warning, the better the chance to contain the contagion. One problem, though, is that governments are sometimes reticent to share information. Such was the case in 2002 and 2003, when Chinese authorities were accused of covering up the SARS epidemic that eventually claimed over 740 lives around the world. With the current outbreak, involving a coronavirus that originated in Wuhan and has so far taken over 40 lives, the Chinese government is being more transparent, as Germany's health minister noted to Bloomberg yesterday on the sidelines of the World Economic Forum in Davos.


Machine Learning and Artificial Intelligence Are Poised to Revolutionize Asthma Care - Pulmonology Advisor

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The advent of large data sets from many sources (big data), machine learning, and artificial intelligence (AI) are poised to revolutionize asthma care on both the investigative and clinical levels, according to an article published in the Journal of Allergy and Clinical Immunology. During 15-minute clinic visits, only a short amount of time is spent understanding and treating what is a complex disease, and only a fraction of the necessary data is captured in the electronic health record. "Our patients and the pace of data growth are compelling us to incorporate insights from Big Data to inform care," the researchers posit. "Predictive analytics, using machine learning and artificial intelligence has revolutionized many industries," including the healthcare industry. When used effectively, big data, in conjunction with electronic health record data, can transform the patient's healthcare experience.


r/MachineLearning - [R] Pigeons classify breast cancer as well as humans

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I've always wondered if we could somehow use animals superior sense of vision to understand artificial neural networks better. Eagles have incredible spatial resolution, and understanding how they viewed adversarial samples might shed more light on the effect of spatial resolution for adversarial samples.


Elsevier Launches 'AI and Big Data in Cancer,' a New Conference on the Translation of Technology, Data and Analytic Innovations into Clinical Practices and Patient Benefits

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AI and Big Data in Cancer: From Innovation to Impact, a new conference from Elsevier, a global information and analytics business specializing in science and health, will bring together experts from all aspects of cancer research and the digital medicine value chain to understand how to translate artificial intelligence and data-driven innovations into new clinical care practices for patients. These leaders, including 2018 Nobel laureate for Medicine, Dr. James Allison, will share pragmatic insights on finding the right partners to move innovations successfully forward. "It is time to shift our conversation from'what-technology-can-do' to'what-medicine-needs' and to raise awareness of what else is necessary to translate an AI-enabled and data-driven innovation into a marketed product," said Dr. Lynda Chin, Conference Chair, Founder and CEO of Apricity Health and Professor at Dell Medical School at the University of Texas, USA. "Understanding what these hurdles are is the first step to overcoming them. "The aim of this conference is to bring innovators together with stakeholders, from patients, clinicians and developers to regulators, payers and investors, so they can network and identify collaborators who can help them accelerate the translation of their innovation into clinical practices," Dr. Chin said. "Insights from the program's 40 key opinion leaders will advance the emerging digital medicine industry, building bridges from computer to clinics," said Laura Colantoni, Vice President for Reference Content, Elsevier, and one of the main organizers for the conference. "We are particularly excited about establishing this conference as a venue for successful innovators, influential facilitators, regulators and payers, as well as investors to find, engage and collaborate with clinicians, researchers and patients to accelerate progress in this area.


An AI Epidemiologist Sent the First Warnings of the Wuhan Virus

#artificialintelligence

On January 9, the World Health Organization notified the public of a flu-like outbreak in China: a cluster of pneumonia cases had been reported in Wuhan, possibly from vendors' exposure to live animals at the Huanan Seafood Market. The US Centers for Disease Control and Prevention had gotten the word out a few days earlier, on January 6. But a Canadian health monitoring platform had beaten them both to the punch, sending word of the outbreak to its customers on December 31. BlueDot uses an AI-driven algorithm that scours foreign-language news reports, animal and plant disease networks, and official proclamations to give its clients advance warning to avoid danger zones like Wuhan. Speed matters during an outbreak, and tight-lipped Chinese officials do not have a good track record of sharing information about diseases, air pollution, or natural disasters.