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Parkinson's Disease


Redefining success in business with Artificial Intelligence

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For unleashing the full potential of Artificial Intelligence (AI), contemporary leadership that can augment AI and humans instead of strategizing to replace AI with humans is the need of the hour from a balanced social, legal, economic, political, and technological perspective. It is a pre-requisite for the organization in the current scenario post-pandemic to realign the business processes with AI considering adaptability, complexity, scalability, decision making, and customization of products and services. For example, in Morgan Stanley Robo-advisors offers clients an array of investment options based on real-time market information, in Pfizer wearable sensors for Parkinson's patients, track symptoms 24/7 allowing customized treatment and in Unilever automated applicant screening vividly inflates the pool of qualified candidates for hiring managers to appraise. According to Harvard business review, it is predicted that the performance and bottom line of organizations is enhanced when humans and AI augment each other leading to enhancing life skills of individuals and teams and technical skills of machines with the right fusion of learning and development activities. Pandemic and resultant transformations have fast-tracked the mechanization of many everyday jobs, with future skepticism towards artificial intelligence (AI) adding to the increase in the rate of unemployment. In reality, if actions are taken appropriately and strategically by the organizations and government combined the reverse might be true that is AI will add to more jobs.


PreciseDx's AI-Enabled Digital Pathology Proven to Detect Early-Stage Parkinson's Disease

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Diagnosing Parkinson's disease is challenging at all stages due to variable symptoms, comorbidities, and mimicking conditions, with definitive diagnosis only coming postmortem. This groundbreaking study found that PreciseDx's AI-enabled technology is able to facilitate a conclusive diagnosis of Parkinson's, providing critical information for earlier treatment. PreciseDx's AI Morphology Feature Array was able to detect Parkinson's pathology in image patches from biopsy samples with 99% sensitivity and 99% specificity as compared to expert annotated ground truth. The AI edged out the human pathologist with an accuracy of 0.69 versus 0.64 in the prediction of clinical Parkinson's disease status. PreciseDx's MFA approach to feature extraction and analysis enables new algorithms to be developed and validated against clinical endpoints.


AI Speeds Precision Medicine for Parkinson's Disease

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Artificial intelligence (AI), machine learning, and robotics are accelerating precision medicine for neurodegenerative diseases and brain disorders. A new study published in Nature Communications reveals a high-throughput screening platform using AI deep learning that finds cellular disease signatures to help accelerate the discovery of novel therapeutics for Parkinson's disease (PD). "To our knowledge, this is the first successful demonstration in which automated, unbiased deep learning-based phenotypic profiling is able to discriminate between primary cells from PD patients (both sporadic and LRRK2) and healthy controls," wrote the study authors affiliated with The New York Stem Cell Foundation Research Institute (NYSCF) and Google Research. Over 10 million people worldwide are living with Parkinson's disease, including nearly a million Americans, according to the Parkinson's Foundation, a nonprofit organization. Parkinson's disease is an incurable, progressive nervous system disorder that affects movement.


Bayer reloads Leaps with €1.3 billion to step up investments in biotech innovation - MedCity News

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Over the past seven years, Bayer's investment arm has infused 50-plus companies with more than €1.3 billion. Leaps by Bayer is accelerating its dealmaking pace and Bayer is committing another €1.3 billion, which the multinational corporation estimates will fuel its investment vehicle for two more years. Bayer announced the capital commitment on Friday during the company's Breakthrough Innovation Forum, an event that covered the corporation's plans in healthcare and agriculture. Those two fields were the core focus areas when Bayer formed Leaps in 2015, aiming to invest in companies developing breakthrough solutions to big challenges facing humanity, challenges that the corporation termed "leaps." At the start, Bayer identified 10 leaps.


Teens Develop Handwriting-Recognition AI for Detecting Parkinson's Disease

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When Tanish Tyagi published his first research paper a year ago on deep learning to detect dementia, it started a family-driven pursuit. Great-grandparents in his family had suffered from Parkinson's, a genetic disease that affects more than 10 million people worldwide. So the now 16-year-old turned to that next, together with his sister, Riya, 14. The siblings, from Short Hills, New Jersey, published a research paper in the fall about using machine learning to detect Parkinson's disease by focusing on micrographia, a handwriting disorder that's a marker for Parkinson's. They aim to make a model widely accessible so that early detection is possible for people around the world with limited access to clinics.


Applications of Deep Learning in medical disorder detection

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This is a review of deep learning oriented papers done as a part of the course COMSE6998 (Practical Deep Learning System Performance) at Columbia University in Spring 2022. This was done under the guidance of our professor at Columbia University, Prof. Parijat Dube. In this article I discuss the first two diseases. The other two will be covered by my team member. Deep learning has recently been applied to analyze neuroimages such as structural MRI and functional MRI and it has outperformed classical machine learning in computer-aided diagnosis of brain illnesses. Now that we know how to evaluate all the deep learning models, let us dive into the first paper.


Artificial intelligence and robotics uncover hidden signatures of Parkinson's disease

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NEW YORK, NY (March 25, 2022) – A study published today in Nature Communications unveils a new platform for discovering cellular signatures of disease that integrates robotic systems for studying patient cells with artificial intelligence methods for image analysis. Using their automated cell culture platform, scientists at the NYSCF Research Institute collaborated with Google Research to successfully identify new cellular hallmarks of Parkinson's disease by creating and profiling over a million images of skin cells from a cohort of 91 patients and healthy controls. "Traditional drug discovery isn't working very well, particularly for complex diseases like Parkinson's," noted NYSCF CEO Susan L. Solomon, JD. "The robotic technology NYSCF has built allows us to generate vast amounts of data from large populations of patients, and discover new signatures of disease as an entirely new basis for discovering drugs that actually work." "This is an ideal demonstration of the power of artificial intelligence for disease research," added Marc Berndl, Software Engineer at Google Research. "We have had a very productive collaboration with NYSCF, especially because their advanced robotic systems create reproducible data that can yield reliable insights."



Hidden Signatures of Parkinson's Disease Uncovered by Artificial Intelligence and Robotics

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New York Stem Cell Foundation (NYSCF) Research Institute collaborates with Google Research to identify new cellular characteristics of disease in skin cells from Parkinson's patients. A study published today (March 25, 2022) in Nature Communications unveils a new platform for discovering cellular signatures of disease that integrates robotic systems for studying patient cells with artificial intelligence methods for image analysis. Using their automated cell culture platform, scientists at the NYSCF Research Institute collaborated with Google Research to successfully identify new cellular hallmarks of Parkinson's disease by creating and profiling over a million images of skin cells from a cohort of 91 patients and healthy controls. "Traditional drug discovery isn't working very well, particularly for complex diseases like Parkinson's," noted NYSCF CEO Susan L. Solomon, JD. "The robotic technology NYSCF has built allows us to generate vast amounts of data from large populations of patients, and discover new signatures of disease as an entirely new basis for discovering drugs that actually work." "This is an ideal demonstration of the power of artificial intelligence for disease research," added Marc Berndl, Software Engineer at Google Research.


Dr. Stephanie Seneff: Covid-19 Vaccines and Neurodegenerative Disease

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Dr. Seneff is a Senior Research Scientist at MIT's Computer Science and Artificial Intelligence Laboratory in Cambridge, Massachusetts, USA. She has a BS from MIT in biology and MS, EE, and PhD degrees from MIT in electrical engineering and computer science. Her recent interests have focused on the role of toxic chemicals and micronutrient deficiencies in health and disease, with a special emphasis on the pervasive herbicide, glyphosate, and the mineral, sulfur. This is an edited segment from the weekly live General Assembly meeting on January 3, 2022. The full meeting can be viewed here. This clip is also available on Rumble and Odysee. "Thank you so much Dr. Seneff!!! Genius presentation, so many important information brought to us easy to understand." -Dr. "Thank you for your important work. The mitigating treatments are hopeful for those who have been coerced into accepting these injections." "Dr Seneff, I hope you will come back and tell us more about your work and the mechanism for the other types of harms that your work has predicted." "Thank you so much, Dr. Seneff." -Helena K "Thank you Dr Seneff, amazing presentation." "Thank you Dr Seneff, that was amazing!" -Dr Tess Lawrie "Beautiful and substantial presentation – thank you, Dr. Seneff!" – Susan I just want to read this quote at the end of this book "The Real Anthony Fauci" and it's because it's Martin Luther King Jr.