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How Artificial Intelligence can help doctors

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Automation through Artificial Intelligence (AI) has made the healthcare industry more efficient and sustainable. Not only it improves the recovery time with no post operative complications in patients but also eases off the work of a surgeon.


How Artificial Intelligence can help doctors

#artificialintelligence

New Delhi [India], Feb 25 (ANI): Automation through Artificial Intelligence (AI) has made the healthcare industry more efficient and sustainable. Not only it improves the recovery time with no post operative complications in patients but also eases off the work of a surgeon.


The Future of Medicine: 3D Printers Can Already Create Human Body Parts

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In recent years, updates in 3D printing technologies have allowed medical researchers to print things that were not possible to make using the previous version of this technology, including food, medicine, and even body parts. In 2018, doctors from the Ontario Veterinary College 3D printed a custom titanium plate for a dog that had lost part of its skull after cancer surgery. "By performing these procedures in our animal patients, we can provide valuable information that can be used to show the value and safety of these implants for humans", said veterinary surgical oncologist Michelle Oblak at the time. "These implants are the next big leap in personalized medicine that allows for every element of an individual's medical care to be specifically tailored to their particular needs." However, instead of depositing materials such as plastic or ceramic, they deposit layers of biomaterial, including living cells, to build complex structures like blood vessels or skin tissue.


Orthopedic field awaits impact of artificial intelligence

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Since the 1950s when the term artificial intelligence was coined, its application and use has increased through rapid technological advances and has found their way into the health care sector, including orthopedics. A study published in 2018 showed the amount of orthopedic literature on machine learning, which is one type of artificial intelligence (AI), had an approximate tenfold increase since 2010, with the most frequently applied machine learning algorithms found in spine pathology, osteoarthritis detection and prediction, and imaging of bone and cartilage. "I think there has definitely been an increase in our understanding but also our attraction or fascination with how [artificial intelligence] may shift care in orthopedics going forward," Atul F. Kamath, MD, director of the Hip Preservation Center, staff in the Orthopedic and Rheumatologic Institute and professor of orthopedic surgery at Cleveland Clinic, told Orthopedics Today. "I think qualitatively, whether you are a lay person or someone in the medical field, you know artificial intelligence is integrated into multiple facets of daily life with autonomous cars and Siri, but also has merged into the medical world with projects like IBM Watson and Google platforms." An increase in larger datasets along with the convergence of cloud-based computing and graphical processing units (GPUs) with other areas of technology have allowed AI to become what it is today, according to Joseph H. Schwab, MD, chief of spine surgery and associate professor of orthopedic surgery at Harvard Medical School and Massachusetts General Hospital.


Endothelial cell adaptation in regeneration

Science

Endothelial cells (ECs) cover the inner wall of blood and lymph vasculature in normal and malignant tissues. It is widely appreciated that ECs are endowed with unique phenotypic, structural, functional, and angiocrine secretory attributes, generating specialized vascular subpopulations with organotypic and diseased-tissue signatures (1, 2). To achieve this high level of organ and tumor heterogeneity, ECs have acquired malleable cellular features that allow them to adapt to normal physiological stressors and to promote tissue homeostasis and regeneration. This is exemplified during liver regeneration in which defined angiocrine (meaning EC-derived) signals from liver sinusoidal ECs initiate and resolve liver regeneration through paracrine signaling to hepatocytes. By contrast, stressed and irritated ECs maladapt to a pathological microenvironment, such as inflamed or chronically injured tissues, favoring fibrosis and tumorigenesis.