Cigniti Technologies, the world's leading AI and IP-led Digital Assurance and Digital Engineering services company, has unveiled a new brand identity reflecting its renewed vision to help its clients in accelerating their digital transformation journeys and achieve market leadership. The new brand identity reflects Cigniti's strengthened resolve to be a trusted digital transformation partner for its clients, including 60 of its Fortune 500 and 80 of its Global 2000 companies, delivering at a global scale with increasingly localized capabilities, and leveraging quality-first digital assurance, product engineering, AI, ML, data and insights, data visualization, automation, and blockchain. In addition to conveying the futuristic vision, the new logo aspires to uphold a contemporary attitude, produce a powerful visual depiction of a shift toward digitalization, and at the same time imbibe the company's software quality-first mindset. Additionally, it aims to exemplify the intense commitment and forward-thinking transformation that the business is embracing through innovation, automation, and artificial intelligence. The company's digital thinking and digital avatar are a reflection of its ability to engineer, assure, and technologically transform and accelerate outcomes for global companies, helping them achieve market leadership in their chosen lines of business.

Bot Image’s ProstatID program recognizes and measures the volume of the prostate gland and highlights suspicious lesions that could be harboring tumor cells.

A new diagnostic tool uses artificial intelligence to detect oral and throat cancers from saliva samples with more than 90 per cent accuracy. Estimates suggest there will be 54,000 new cases of oral cancer and 20,640 new cases of oesophageal cancer in the US alone this year. The respective 5-year survival rates for these cancers are 68 and 20.6 per cent, but when detected early, those numbers jump to more than 86 and 47 per cent. The issue is that most oral and throat cancers aren't detected early. Current screening methods rely on visual examinations by a healthcare provider.

During the past 10 years, antisense-mediated exon skipping has proven to be a powerful tool for correction of mRNA splicing. For example, recently FDA-approved antisense oligonucleotides, including viltolarsen, eteplirsen, golodirsen, and milasen, were developed based on exon skipping technology. A significant challenge, however, is the difficulty in selecting an optimal target sequence for exon skipping. We have developed a computational method that takes into account many parameters as well as experimental data to design highly effective ASOs for exon skipping1, and improved this frame using a machine-learning algorithm. Shuntaro Chiba and Yasushi Okuno at the Molecular Design Data Intelligence Unit, RIKEN, Dr. Yoshitsugu Aoki at the Department of Molecular Therapy, National Center of Neurology and Psychiatry, and Dr.Toshifumi Yokota at the Department of Medical Genetics, University of Alberta, Faculty of Medicine and Dentistry. 1 Echigoya Y, Mouly V, Garcia L, Yokota T, Duddy W, In Silico Screening Based on Predictive Algorithms as a Design Tool for Exon Skipping Oligonucleotides in Duchenne Muscular Dystrophy.

Viz Subdural Hematoma (SDH), a new artificial intelligence (AI)-powered algorithm for diagnosing subdural hemorrhages, has garnered 510(k) clearance from the Food and Drug Administration (FDA), according to Viz.ai, the manufacturer of the module. Noting a rising incidence of subdural hematomas, Viz.ai said the SDH algorithm demonstrated sensitivity and specificity rates of 94 and 92 percent respectively in a multicenter trial of over 500 patients.1,2 "The algorithm is very sensitive and specific, significantly increasing the number of subdural hemorrhages detected and ensuring patients receive the necessary follow-up from this potentially life-threatening disease," maintained Jayme Strauss, the chief clinical officer at Viz.ai. The company emphasizes that Viz SDH is currently the only AI-powered platform specifically geared to identifying and differentiating between acute and chronic subdural hemorrhages. Jason Davies, M.D., Ph.D., said this is a key benefit given the different treatment pathways for these conditions.

Vaccinations against viruses have always been the need of the hour since long past. However, it is hard to efficiently distribute the vaccines (on time) to all the corners of a country, especially during a pandemic. Considering the vastness of the population, diversified communities, and demands of a smart society, it is an important task to optimize the vaccine distribution strategy in any country/state effectively. Although there is a profusion of data (Big Data) from various vaccine administration sites that can be mined to gain valuable insights about mass vaccination drives, very few attempts has been made towards revolutionizing the traditional mass vaccination campaigns to mitigate the socio-economic crises of pandemic afflicted countries. In this paper, we bridge this gap in studies and experimentation. We collect daily vaccination data which is publicly available and carefully analyze it to generate meaning-full insights and predictions. We put forward a novel framework leveraging Supervised Learning and Reinforcement Learning (RL) which we call VacciNet, that is capable of learning to predict the demand of vaccination in a state of a country as well as suggest optimal vaccine allocation in the state for minimum cost of procurement and supply. At the present, our framework is trained and tested with vaccination data of the USA.

Viz.ai announced it has received U.S. Food and Drug Administration (FDA) 501(k) clearance for Viz SDH, which uses artificial intelligence (AI) to detect subdural hemorrhage (SDH). By detecting SDH automatically, Viz SDH allows physicians to triage patients effectively and deliver care, according to the company. Viz.ai notes that subdural hemorrhage is projected to become the most common neurosurgical diagnosis by 2031, and global clinical trials are investigating new treatments to address this disease. Viz SDH has the capability to identify acute and chronic subdural bleeds and notify the care team in the event of a necessary immediate intervention, according to Viz.ai.

Pearl, the leader in dental AI solutions, and Midway Dental, one of the leading dental technology and supply distributors in the United States, announced that Pearl is now Midway's preferred artificial intelligence (AI) solutions provider. Pearl's Practice Intelligence AI solution is already available as part of Midway's cutting-edge product sales and distribution inventory, and the collaboration will now also include Second Opinion, the first and only FDA-cleared chairside AI software to help dentists detect numerous conditions in x-rays of dental patients 12 and older. "Our partnership with Midway ensures that forward-thinking dental practices across the U.S. have access to the most advanced AI to streamline their practice management and real-time chairside radiologic evaluations" With over 15,000 dental customers, Michigan-based Midway Dental is the fastest growing full-service dental supply company in the United States, aiming to transform the dental supply industry into something new and progressive. By selecting Pearl as its preferred AI service provider, Midway has reaffirmed its commitment to empowering dental care providers with the most advanced dental technologies for better patient communication, trust, and treatment outcomes. "We selected Pearl as our preferred AI service provider because it is the only dental AI company that can actually deliver on AI's promise for our customers," said Steve Kizy, president of Midway.

Redwood City, California-based Exo intends to integrate Medo's proprietary Sweep AI technology into its ultrasound platform to make the imaging modality more accessible to a wider range of caregivers. No financial terms for the acquisition were disclosed. According to a news release, Canada-based Medo's ultrasound AI technology radically lowers the expertise required to diagnose common and critical conditions through automated image acquisition and interpretation, giving non-experts the ability to conduct high-quality exams quickly and accurately. The company brings with it two FDA-cleared AI algorithms, as well as more in development, plus access to an extensive library of millions of ultrasound images and longitudinal health data to speed up point-of-care ultrasound adoption across the healthcare system, potentially expanding early disease detection and accelerating the path to treatment. Medo also holds strong partnerships across health systems worldwide, Exo said, including top institutions in Asia and Canada that can help to enable clinical validation and adoption.

Rapid new drug discovery had never been more critical in a world with an aging population and increased instances of infectious diseases. While traditional lab methods have proven reliable, the recent covid-19 pandemic has shown the need for further innovation. The global drug discovery market size was valued at US$ 74.96 billion in 2021.[1] Despite such massive investments, the number of new drugs approved by the FDA remains low. Current drug discovery methods are slow, expensive, dominated by big pharma, and require cruel animal testing procedures.