As former President Donald Trump awaits a Manhattan jury's verdict, he can be forgiven for feeling that his criminal trial resembles a surreal "Alice in Wonderland" farce. He is left to peer through a "Looking-Glass" where everything is backward. The culprit for this hallucinatory nightmare is District Attorney Alvin Bragg who brought a bizarre case based on warped interpretations of law and distorted facts. It is now up to twelve jurors to wade through the lunacy in search of the illusive truth. Bragg's fractured case requires the jury to reach several distinct conclusions on issues that make little sense to begin with.

The US federal government spends more than a trillion dollars per year on health care, largely provided by private third parties and reimbursed by the government. A major concern in this system is overbilling, waste and fraud by providers, who face incentives to misreport on their claims in order to receive higher payments. In this paper, we develop novel machine learning tools to identify providers that overbill Medicare, the US federal health insurance program for elderly adults and the disabled. Using large-scale Medicare claims data, we identify patterns consistent with fraud or overbilling among inpatient hospitalizations. Our proposed approach for Medicare fraud detection is fully unsupervised, not relying on any labeled training data, and is explainable to end users, providing reasoning and interpretable insights into the potentially suspicious behavior of the flagged providers. Data from the Department of Justice on providers facing anti-fraud lawsuits and several case studies validate our approach and findings both quantitatively and qualitatively.

Managing expenses isn't a task that many people particularly love to work on, yet it's a vital one and can have enormous ramifications for a business if not handled properly. If you'd like to find a way to spend less time sorting out this area of your organizational finances and reduce problems simultaneously, it's worth turning to technology. Thanks to artificial intelligence (AI), expense management is becoming easier and more effective than ever. In many organizations, a lack of space or too much paperwork to store leads to a lot of stress and time spent attempting to locate files. If this is a pain point in your venture, AI can help at least limit expense-based paperwork, among other things.

Keith J. Dreyer, DO, PhD, FACR, American College of Radiology (ACR) Data Science Institute Chief Science Officer, explains the state of artificial intelligence (AI) in radiology in 2022. Although there are about 200 AI algorithms for medical imaging now cleared by the U.S. Food and Drug Administration (FDA), a recent ACR survey of its members showed AI only has about a 2% market penetration rate. "So, there is about another 98% that fall into the category of potential addressable market," Dreyer said. "Now why is that when there is a lot of enthusiasm and we are past the days from six years ago when radiologists were fearful of losing their jobs to AI because Geoffrey Hinton said we should stop training radiologists because AI will take over in another 5 years. That was in 2016, and are now past the five-year mark and it's ridiculous, because today there is an incredible shortage of radiologists."

Here at Hugging Face, we're on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source, library of pre-trained models in the world. With over 100M installs and 65K stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. You will work extremely closely with the CTO, help him stay on top of everything, explore new Machine Learning Adhoc topics that require someone's full attention, help coordinate communication across the company and externally (social media).

In development for more than a year, Auto-Itemization from TripActions Liquid is a solution that automatically splits transactions and attributes each line item to specific expense policies. The technology allows a user to upload a receipt for automatic itemisation; using AI, foreign language translation and fuzzy matching, each line item is categorised and assigned to a specific policy with 90 per cent accuracy. The use of machine learning also ensures that accuracy will increase over time. Single transactions often consist of multiple parts or line items -- like variable daily service charges for a hotel stay -- that need to be reported independently for accounting and tax purposes. The cost of the room needs to align with a company's hotel policy, while the room service that employee orders can align to a per diem for meal costs.

Health care information technology company Netsmart has purchased Remarkable Health, a Chandler, Arizona-based provider of artificial intelligence (AI) technology and software solutions for organizations focused on behavioral health and individuals with intellectual and developmental disabilities (I/DD). Terms of deal, which was announced Thursday, were not disclosed. Remarkable Health's products include CT One -- a management platform for behavioral health claims and records -- and Bells, a notetaking documentation solution for behavioral health clinical staff. Remarkable Health's products will complement that of Netsmart's CareFabric platform, an operating system that includes resources such as electronic health records and management tools, and which are utilized by providers like those in behavioral health, addiction treatment and autism care. Remarkable Health claims that the Bells platform helps reduce time spent on clinical documentation by over 50%, enabling organizations to serve six more clients per month.

All businesses need a system to accurately track their expenses. Without it, they would not be able to keep reliable records and would likely soon find themselves in financial trouble. To track expenses, most businesses rely on some form of expense management software. However, not all expense management software options are created equal. One such example is expense management software that's powered by AI.

Prior to the coronavirus pandemic, the use of digital technology in healthcare was on a steady rise; however, the pandemic has spurred rapid development of digital health technology as well as rapid adoption and utilization of that technology in the industry. Digital health holds the promise of increased accessibility to high-quality, patient-centered care that can also increase patient engagement and reduce costs. However, the full realization of this promise may be threatened by policy and regulation that is failing to keep pace with and encourage this evolution. There is no universally accepted definition of digital health. In fact, researchers studying the definition recently came across no fewer than 95 published definitions for the concept of digital health.1 There were, however, some clear patterns: there is an emphasis on how data is used to improve care; there is a focus on the provision of healthcare, rather than the use of technology; and the definitions tend to highlight the well-being of people and populations over the caring of patients with diseases. As used in this article, digital health encompasses the use of digital tools and technologies to improve and manage an individual's or a population's health and wellness.

The current COVID-19 public health crisis has converged with the racial and socioeconomic injustices that plague our society, highlighting vast differences in health care access. Though the U.S. spends more on health care than any other developed nation, access to critical preventive care remains particularly challenging for many racial and ethnic minority populations, as well as lower-income and rural Americans. For many, visits to a specialist for a routine diagnostic exam represent a time-consuming and costly venture. As a result, many serious conditions go undiagnosed until they are advanced when treatment becomes more expensive and invasive, and outcomes are less favorable. In 2019 a record number of U.S. adults (33 percent) said they put off receiving medical care due to cost, according to Gallup's annual Health and Healthcare poll.