Artificial Intelligence In Healthcare

Faced with the modern-day challenges of healthcare it is becoming increasingly more difficult to practice value-based medicine in today’s climate of volume-based medicine. Over the past decade, we’ve seen health systems around the world experience significant strain due to increasing population numbers and age. There is a clear need to maximize efficiency, lighten the burden of stretched human resources and harness the medical sector’s mountains of data.

Since it is unlikely, in the near future, that administrators will tell radiologists to forget about metrics and relative value units (RVUs), and instead focus on providing a value-based interpretation for the patient, new solutions are needed to deal with the increasing workload challenges while continuing to provide value for the patient and referring clinician.

Fortunately, we now live in an exciting time of deep learning, and solutions are on the horizon. Artificial Intelligence has in fact been around since the 1950’s. Slowly but surely, artificial intelligence is infiltrating almost every aspect of our lives. It is already busy in the background of many routine tasks, powering virtual assistants like Siri and Alexa, recommendations from Amazon and Netflix, and underpinning billions of Google searches each day. But as the technology matures, AI’s impact will become more profound, and nowhere is that more apparent than in healthcare.

It is not an exaggeration to say that the potential for this technology to enhance the way we manage and treat illness is almost unimaginable today. Today’s smart-tech monitors everything from blood sugar to heart pressure. It is not unreasonable to think that by 2050, the laboratory of the future will not be in a pharmaceutical lab but a patient’s own body, where AI highlights health risks, enabling humans to make better care decisions. Tech start-ups all over are trying to address social needs and disabilities from a technological standpoint. Blindness and deafness are two such ailments, and AI startup Halfcode seeks to launch a product that will aid those visually and/or hearing impaired.

Although it’s clear to see the future revolutionary potential, AI in healthcare is still in its infancy. Still, AI research is moving quickly on a multiplicative logarithmic trajectory. Applications that didn’t exist two years ago are now available. Prior challenges are becoming strengths, which are leading to advances in radiology and medicine.

Healthcare’s data-heavy nature makes it an ideal candidate for the application of AI across multiple disciplines, from diagnosis and pathology to drug discovery and epidemiology. At the same time, the sensitivity of medical data raises fundamental questions around privacy and security. This juxtaposition makes healthcare one of AI’s most exciting frontiers.

One of AI’s biggest opportunities in medicine is ‘predictive care guidance’ which allows both patient and healthcare providers to leverage technology and make better decisions when diagnosing patients.

For all this noise, the most promising aspect of AI in healthcare is how it empowers the human element and rekindles the crucial relationship between caregivers, healthcare professionals, payers, and patients. At a time when resources are stretched, these relationships are difficult to maintain, this is where AI jumps in saving time for caregivers and also saving the relation.

The future is bright, and if we can continue to develop creative solutions to improve the care of patients, in collaboration with deep learning algorithms, then we’ll again have succeeded in advancing medicine into a new  healthcare revolution, more evolved and sophisticated, that will continue to benefit both clinicians and patients.

venturebeatblog  beautymagnetism  beautyation  charismaticthings  businessknowledgetoday

Popular posts from this blog

Business Forecasting

  Business Forecasting Business forecasting is the system of predicting destiny trends in commercial enterprises based on evaluating tendencies in beyond and present records.   hollyhealthfitness What is Business Forecasting?  Business forecasting refers to the gear and strategies used to are expecting tendencies in business, inclusive of sales, prices, and profits. The reason for enterprise forecasting is to broaden higher techniques based on these knowledgeable predictions. Past facts are gathered and analyzed through quantitative or qualitative fashions so that patterns may be identified and direct demand-making plans, financial operations, destiny manufacturing, and advertising operations. The enterprise forecasting method entails: Ø   Identify the problem, data factor, or query to be the idea of the systematic investigation. Ø   Identify relevant, theoretical variables and decide the proper manner for collecting datasets. Ø   Make es...
Read more

Emergency Management

  Emergency Management Emergency making plans control refers back to the coordination and management of sources and obligations bearing on the mitigation of, preparedness for, reaction to, and recovery from an emergency. It includes gathering, controlling, and analyzing extensive information to integrate a facts-driven approach into each emergency management cycle section. What is Emergency Management? An emergency management plan's closing purpose is to provide a data-driven framework that allows communities to recognize and reduce vulnerabilities, deal with the aftermath of a disaster, and similarly develop catastrophe reaction plans. Big data in disaster control uses the analysis of records accrued from an affected community in real-time so that you can enhance the efficiency and effectiveness of emergency management reaction teams. Disaster control data series and emergency management software facilitate innovative emergency control endeavors, including disaster mapping...
Read more

Edge Network

  Edge Network Edge networking is a dispensed computing paradigm that brings computation and data storage as close to the point of request as viable, allowing you to deliver low latency and keep bandwidth. What is Edge Network? The goal of network part computing is to bodily pass computation far from data centers toward the community's threshold, therefore reducing the stress on information centers, which are inundated with IoT device statistics and consequently can't usually deliver applicable response times. Creating a side computing community is finished by decentralizing information facilities and exploiting smart items and network gateways to offer offerings on behalf of cloud computing.  techbizcenter Specialized department routers and network part routers positioned at the network boundary generally use dynamic or static routing competencies thru Ethernet to ship or acquire data between the internal and outside community. Moving offerings towards community are...
Read more