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9 Benefits of Using AI in Medical Billing and Coding - MailMyStatements

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Medical billing and coding have been undergoing many changes in recent years as the healthcare industry increases in complexity while the variety of treatments and procedures grow by the minute. The healthcare industry is in urgent need of a scalable solution that can process the vast amount of patient data without compromising speed and accuracy of the billing procedure. The use of artificial intelligence in the medical billing and coding industry can help healthcare organizations facilitate their billing procedures while minimizing costly errors. AI-driven technologies, such as machine learning and natural language processing (NLP), have the ability to interpret and organize a large amount of data quickly and accurately. For instance, an AI program can arrange data from different records into a logical timeline to make sense of disparate events, diagnoses, and procedures, minimizing coding and reporting errors.


10 Exciting Webinars & Workshops In Machine Learning

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However, one of the ways professionals are keeping up their relevance in their organisations as well as in the industry is by upskilling and learning the latest tools and technologies of this evolving field. Webinars and workshops have always been an excellent way for professionals and enthusiasts to keep themselves updated with the latest trends and technologies. For attendees, these webinars and workshops are not only an easy way to know and train themselves on the latest tools and technologies but also allows them to hear from the best minds of the industry on relevant topics. In fact, for a few years now, large tech companies have been conducting free webinars and workshops, which will not only boosts the community and users at large but also acts as a great marketing tool for advertising their solutions and services. With machine learning being explored in various industries, including healthcare, eCommerce, finance and retail, the possibilities are endless.


AI is already building a more resilient post-pandemic world - Watson Blog

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For some organizations, AI tools may have been perceived as "nice-to-have" technologies prior to 2020. In a 2019 IBM/Morning Consult survey of businesses, 22% of respondents worldwide reported they are not currently using or exploring the use of AI. But in a future characterized by uncertainty, only organizations that embrace the most advanced AI tools will be able to weather future storms. The COVID-19 pandemic remains an immediate threat, but all kinds of organizations are looking ahead to build resilient systems that can better withstand future pandemics, as well as natural disasters, cyberthreats, and other destabilizing scenarios. The current crisis is an opportunity to examine the performance of the technological systems that we use to manage the various aspects of human existence.


Democratize AI: Exploring Future of Technology

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When individuals talk about artificial intelligence (AI), the first organizations that ring a bell are typically the FAANGs -- Facebook, Apple, Amazon, Netflix and Google. However, this is a long way from a complete rundown. Anybody can deploy AI today, and the FAANGs have no exceptional bit of leeway. The large technology companies accomplished early victories with artificial intelligence. Some even manufactured their own specific hardware, machine learning frameworks, and research and development centers.


How AI & Data Analytics Is Impacting Indian Legal System

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In a survey conducted by Gurugram-based BML Munjal University (School of Law) in July 2020, it was found that about 42% of lawyers believed that in the next 3 to 5 years as much as 20% of regular, day-to-day legal works could be performed with technologies such as artificial intelligence. The survey also found that about 94% of law practitioners favoured research and analytics as to the most desirable skills in young lawyers. Earlier this year, Chief Justice of India SA Bobde, in no uncertain terms, underlined that the Indian judiciary must equip itself with incorporating artificial intelligence in its system, especially in dealing with document management and cases of repetitive nature. With more industries and professional sectors embracing AI and data analytics, the legal industry, albeit in a limited way, is no exception. According to the 2020 report of the National Judicial Data Grid, over the last decade, 3.7 million cases were pending across various courts in India, including high courts, district and taluka courts.


Can this artificial intelligence program replace writers, journalists and poets?

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Seven years ago, my student and I at Penn State built a bot to write a Wikipedia article on Bengali Nobel laureate Rabindranath Tagore's play "Chitra." First, it culled information about "Chitra" from the internet. Then it looked at existing Wikipedia entries to learn the structure for a standard Wikipedia article. Finally, it summarised the information it had retrieved from the internet to write and publish the first version of the entry. However, our bot did not "know" anything about "Chitra" or Tagore. It did not generate fundamentally new ideas or sentences.


Streaming System Design for Large-Scale Machine Learning Applications

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In October of 2019 Crunchbase raised $30M in Series C financing from OMERS Ventures. Crunchbase is charging forward, focusing more deeply on the analysis of business signals for both private and public companies. Here at the Engineering Team, we have been working on the interesting challenge of detecting these high value business signals from various sources, such as Tweets and news articles. Some examples of important signals include funding rounds, acquisitions, and key leadership hires. Finding these signals the moment they are announced empowers our customers to make well-informed business decisions.


Can This Tiny Language Model Defeat Gigantic GPT3?

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While GPT-3 has been bragging about achieving state-of-the-art performance on Complex NLP tasks with hundred billion parameters, researchers from the LMU Munich, Germany have proposed a language model who can show similar achievements with way fewer parameters. GPT-3 has been trained on 175 billion parameters and thus showed remarkable few-shot abilities, and by reformulating a few tasks and prompting inputs, it also showed immense capabilities on SuperGLUE benchmark. However it comes with two most significant drawbacks -- large models aren't always feasible for real-world scenarios, and with the context window of these monstrous models is limited to a few hundred tokens, it doesn't scale more than a few examples. And thus, the researchers proposed an alternative to priming, i.e. PET required unlabelled data, which is easier to gather than labelled data, thus making it usable for real-world applications.


What is Artificial Intelligence?

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Artificial Intelligence (AI) is a part of our daily lives -- from language translation to medical diagnostics and driverless cars to facial recognition -- it's making more of an impact on industry and society every day. But what exactly is AI? Simply put, AI is a technology that replicates human intelligence through computers, systems or machines. This is a fairly broad description, however, and different people have different ways of interpreting it. Whatever its description, the concept of AI isn't new and has been around since at least 1950. That was when Alan Turing, an influential computer scientist and mathematician, speculated about AI as'thinking machines'. Turing went on to develop the'Turing test', which identifies artificial intelligence based on a machine's ability to do reasoning puzzles with human-like capabilities.


Top 4 Chatbot Myths Debunked - e-bot7

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The quality of customer service is crucial for the success of companies, irrespective of the industry. A study by Forrester Research reports that 66% of the customers won't return if the customer service was bad, making customer service a critical component of a successful business strategy. The growth in the number of chatbot solutions and technologies on the market has led to several myths spreading. With this article, we are going to explore the top four with you. AI-powered chatbots can automate repetitive questions with the best being able to offer a hybrid approach allowing for a dynamic knowledge base that grows as you scale.