Artificial Intelligence, Deep Learning, and Medicine

Proactive Physician stance will save the Art of Medicine

Originally published by Data Driven Investor

Photo by Tanner Boriack on Unsplash

As physicians, nurses, dentists, or any healthcare expert, we all have experienced the earshot of floating buzzwords about the themes of Artificial intelligence (AI), machine learning (ML), and deep learning (DL). But not all of us are mindful of their potential consequences. On the contrary, yet generally speaking, most people, particularly the millennials, seem to be sparkly optimistic about the role of Artificial intelligent technology as being collectively encouraging.

Deep learning is a component of a much more comprehensive group of technology termed machine learning. DL defines the spectrum of artificial neural networks amidst imitation learning. That is why deep learning is also referred to as deep structured learning or differential programming, which can adopt a form of supervised, semi-supervised, or unsupervised modalities. Deep neural networks, deep belief networks, recurrent neural networks, and convolutional neural networks have been mainly applied to domains such as speech recognition, natural language processing, computer vision, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection, and board game programs. Each component of the DL techniques has produced results analogous to human expertise and even better.

In general, the concept of machine learning follows; that the gadget should learn and adapt through experience and execute the tasks “smartly.”

Artificial Intelligence implements whatever is learned through machine learning, deep learning, and other systems to solve substantive predicaments. In the computer science realm, artificial intelligence (AI), also referred to as machine intelligence, is nothing but machines’ capacity to demonstrate what is typical for natural intellect exhibited by humans and animals.

The Utility of Artificial Intelligence, Machine Learning

With Artificial intelligence, today, one can perform an extraordinary spectrum of tasks. Using AI, one can ask questions by voice and get answers about many issues not stereotypically known to everyone. Or The computer can find data that could never come to a person’s mind. Artificial Intelligence, utilizing Deep Learning, will offer a narrative summary of someone’s data and suggest other ways to probe into collected information. Similarly, AI will furthermore distribute information narrated to earlier inquiries from others who asked the same questions. You’ll get the answers on a screen or directly through conversation.

The utility of artificial intelligence and Deep Neural Learning may seem potentially legit and promising, particularly concerning the extension of quality human life. Nonetheless, in realism, the messages portrayed are varied. Indeed, In health care, treatment efficacy can be determined instantly, whereas, in retail, inventories are suggested quickly, or in finance, fraud is prevented instead of just spotted. In every latter scenario, the computer efficiently recognizes what information is necessitated, looks at relationships between all the factors, forms an answer, and automatically communicates it to the users. It provides options for follow-up queries and even carries out additional pre-determined tasks with little human intervention, yet even better.

Every AD, ML, DL technology relies on a set of finite sequences of explicit, computer-implementable instruction or algorithms, which are frequently not disclosed to the public. Consequent to everything mentioned, the notion of Artificial Intelligence utility is a bittersweet experience, as the risk versus benefit of the technology lies within its particular algorithm.

Artificial intelligence delivers the promise of genuine human-to-machine interaction. It magnifies human potential with cumulative precision. The intelligent machines, over time, utilizing various machine learning techniques, can understand requests irrespective of a good deed or evil feat.

Artificial Intelligence help connect data points and draw conclusions irrespective of moral consequence, while they can learn to reason, observe, and plan.

All the advancements from Amazon Alexa to Apple Siri brought artificial intelligence closer to its original goal of creating intelligent machines, which we’re starting to see more and more in our everyday lives. From recommendations on our favorite retail sites to auto-generated photo tags on social media, many ordinary online amenities are powered by artificial intelligence. Further, through advances in AI technologies, we see that the more privacy goes out the door, the more trivial it turns out to be our liberty.

Artificial Intelligence in Healthcare

Artificial intelligence is becoming a transformational force in the healthcare arena, as expected to disrupt healthcare in many ways.

Artificial Intelligence is expected to unify the Human Mind with that of the Machine through an Interface.

Establishing a direct connection between technology and the human brain without using keyboards, mice, and monitors is a state-of-the-art research theme that has abundant applications for patient care. It will, for example, take up some of the responsibilities for kinds of functions that could be potentially taken away by some Neurological diseases and trauma to the nervous system. Or AI will speak for the patient when impaired; otherwise, move his arm if paralyzed.

The Next Generation of Artificial Intelligence will perform Radiological Readings.

Radiological images captured by MRI machines, CT scanners, and x-rays offer non-invasive visibility into the inner workings of the human anatomy. Though several diagnostic processes still rely on direct tissue sampling or tissue biopsy to carry risks of infection and bleeding, AI will enable the next generation of radiology machines thorough enough to omit the need for diagnostic biopsy in selected instances.

Artificial intelligence is enabling “virtual biopsies” by advancing the innovative field of “radionics.” The following science emphasizes harnessing image-based algorithms to portray the phenotypes and genetic properties of tumors.

Artificial Intelligence will maximize Quality Medical Care to Underserved and Rural Communities.

Shortages of qualified physicians, including radiology technicians and radiologists, can potentially curb admittance to life-saving care in developing communities around the globe.

Artificial intelligence could help alleviate the repercussions of a severe deficit of qualified clinical staff by taking over some of the responsibilities typically earmarked to humans.

Electronic Health Records (EHR) can be more efficient using appropriate AI Algorithms.

Electronic health records play a more active part in the healthcare industry’s drive towards documentation and The Health Information Technology for Economic and Clinical Health (HITECH). However, the transition to the digitalization of health records has faced innumerable problems, from cognitive overload, continual documentation to physician burnout.

HITECH industry is now using AI and deep learning to create more intuitive interfaces by automating some of the formal rules that occupy most of the physician’s time. Most likely than not, machine learning and AI may further support preparing conventional requests from the inbox, like medication refills and results from notifications. It may additionally assist in prioritizing tasks that truly require the clinician’s awareness.

Artificial Intelligence will turn a Medical Device into an Independently functioning Robot.

Innovative medical devices are filling up the user scene, allowing everything from real-time video from the inside of an intestine to sensing facial expression for early diagnosis of Autism.</