Oncology


Talking Digital Future: Artificial Intelligence Cointelegraph

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I chose artificial intelligence as my next topic, as it can be considered as one of the most known technologies, and people imagine it when they talk about the future. But the right question would be: What is artificial intelligence? Artificial intelligence is not something that just happened in 2015 and 2016. It's been around for a hundred years as an idea, but as a science, we started seeing developments from the 1950s. So, this is quite an old tech topic already, but because of the kinds of technology that we have access to today -- specifically, processing performance and storage -- we're starting to see significant leaps in AI development. When I started the course entitled, "Foundations of the Fourth Industrial Revolution (Industry 4.0)," I got deeper into the topic of artificial intelligence. One of the differences between the third industrial revolution -- defined by the microchip and digitization -- and the fourth industrial revolution is the scope, velocity and breakthroughs in medicine and biology, as well as widespread use of artificial intelligence across our society. Thus, AI is not only a product of Industry 4.0 but also an impetus as to why the fourth industrial revolution is currently happening and will continue to do so. I think there are two ways to understand AI: the first way is to try giving a quick definition of what it is, but the second is to also think about what it is not.


Daily Digest March 27, 2020 – BioDecoded

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Radiologic screening of high-risk adults reduces lung-cancer-related mortality; however, a small minority of eligible individuals undergo such screening in the United States. The availability of blood-based tests could increase screening uptake. Here researchers introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq), a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. They show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. They develop and prospectively validate a machine-learning method termed'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls.


Integrating genomic features for non-invasive early lung cancer detection

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Radiologic screening of high-risk adults reduces lung-cancer-related mortality1,2; however, a small minority of eligible individuals undergo such screening in the United States3,4. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)5, a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent.


Talking Digital Future: Artificial Intelligence

#artificialintelligence

Quantum computing could potentially break much of the encryption algorithms and protocols that currently secure the internet and computational industry as they are. I chose artificial intelligence as my next topic, as it can be considered as one of the most known technologies, and people imagine it when they talk about the future. But the right question would be: What is artificial intelligence? Artificial intelligence is not something that just happened in 2015 and 2016. It's been around for a hundred years as an idea, but as a science, we started seeing developments from the 1950s. So, this is quite an old tech topic already, but because of the kinds of technology that we have access to today -- specifically, processing performance and storage -- we're starting to see significant leaps in AI development. When I started the course entitled, "Foundations of the Fourth Industrial Revolution (Industry 4.0)," I got deeper into the topic of artificial intelligence. One of the differences between the third industrial revolution -- defined by the microchip and digitization -- and the fourth industrial revolution is the scope, velocity and breakthroughs in medicine and biology, as well as widespread use of artificial intelligence across our society. Thus, AI is not only a product of Industry 4.0 but also an impetus as to why the fourth industrial revolution is currently happening and will continue to do so.


Talking Digital Future: Artificial Intelligence

#artificialintelligence

I chose artificial intelligence as my next topic, as it can be considered as one of the most known technologies, and people imagine it when they talk about the future. But the right question would be: What is artificial intelligence? Artificial intelligence is not something that just happened in 2015 and 2016. It's been around for a hundred years as an idea, but as a science, we started seeing developments from the 1950s. So, this is quite an old tech topic already, but because of the kinds of technology that we have access to today -- specifically, processing performance and storage -- we're starting to see significant leaps in AI development. When I started the course entitled, "Foundations of the Fourth Industrial Revolution (Industry 4.0)," I got deeper into the topic of artificial intelligence. One of the differences between the third industrial revolution -- defined by the microchip and digitization -- and the fourth industrial revolution is the scope, velocity and breakthroughs in medicine and biology, as well as widespread use of artificial intelligence across our society. Thus, AI is not only a product of Industry 4.0 but also an impetus as to why the fourth industrial revolution is currently happening and will continue to do so. I think there are two ways to understand AI: the first way is to try giving a quick definition of what it is, but the second is to also think about what it is not.


New AI-powered blood test could reveal lung cancer without a CT scan

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A team of scientists in the United States has developed a blood test that uses machine learning to hunt for the telltale signs of lung cancer. The system, which is still early in its development, could eventually replace CT scans as a first-line screening measure for suspected lung cancer patients. The test hunts for tumor DNA that is circulating in a person's blood, and is far less expensive than CT scans which are typically used to diagnose lung cancer. It's not yet ready to be used on a widespread basis or relied upon in real-world settings, but the research is incredibly promising and could prove to be a powerful weapon against one of the deadliest types of cancer. Medical researchers and doctors already know that cancer DNA circulating in a patient's bloodstream could serve as a tool for diagnosing the disease.


Patients may be receptive to skin cancer screening via artificial intelligence

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Three-quarters of patients would recommend artificial intelligence as a component of clinical decision-making for skin cancer, according to a survey. "The use of artificial intelligence (AI) is expanding throughout the field of medicine," Caroline A. Nelson, MD, of the department of dermatology at Yale School of Medicine, and colleagues wrote, adding that researchers are investigating the use of AI in classifying skin lesions. "Although AI is poised to change how patients engage in health care, patient perspectives remain poorly understood." The researchers conducted semi-structured interviews with 48 patients in general dermatology clinics at Brigham and Women's Hospital and melanoma clinics at Dana-Farber Cancer Institute to determine how patients think about the risks, benefits, strengths and weakness of AI as it pertains to skin cancer screening. They also aimed to determine how patients feel about the differences between human and AI clinical decision-making.


Outcomes Rocket Healthcare Using AI and Machine Learning

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When you hear the words artificial intelligence, what's the first thing that comes to mind? Driverless cars, Amazon shopping, Netflix movie recommendations and trading software to help bankers. Many think of artificial intelligence in healthcare as a buzz word or just a concept that will fully develop in the near future, but has no impact in your life right now. Some other household examples of current-day technology that use AI include Siri, Alexa, Google Now – these popular speech recognition software assistants all use artificial intelligence! Recently, Alexa was cleared to handle patient information.


Artificial Intelligence Supports Clinical Operations in Oncology Studies

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As the pharmaceutical and medical care industries move toward adoption of artificial intelligence technologies, new possibilities are arising for improvements in drug trials through streamlined clinical operations processes. Worldwide Clinical Trials' recent partnership with Deep Lens could provide evidence of how future drug studies can benefit from AI-driven technologies. A recent study estimates the average dropout rate for all clinical trials at 30%.1 Such patient discontinuation can necessitate exponential increases in patient numbers to achieve required levels of statistical significance. The goal is to minimize additional recruitment costs and delays by improving efficiencies during study execution. As clinical trial stakeholders seek to streamline clinical processes, artificial intelligence emerges as an innovative approach to improving patient monitoring and clinical care, as well as enhancing and accelerating end point detection.


Futuristic Artificial Intelligence – Less Artificial, More Intelligent

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Artificial Intelligence has had its impact virtually on every industry and human being. AI is considered the main driver of emerging technologies like big data, robotics, and the Internet of Things (IoT), and will act as a technological innovator in the foreseeable future. The impact AI is having on our present lives is hard to ignore, be it in sectors such as transportation, manufacturing, healthcare, education, media, and customer service. However, AI in these sectors is all nascent, and the true self of artificial intelligence will unfold itself in the future as more and more companies are investing hard on AI technology. Companies are spending close to $20 billion on AI products and services annually.