Motivation: In this paper we present the latest release of EBIC, a next-generation biclustering algorithm for mining genetic data. The major contribution of this paper is adding support for big data, making it possible to efficiently run large genomic data mining analyses. Additional enhancements include integration with R and Bioconductor and an option to remove influence of missing value on the final result. Results: EBIC was applied to datasets of different sizes, including a large DNA methylation dataset with 436,444 rows. For the largest dataset we observed over 6.6 fold speedup in computation time on a cluster of 8 GPUs compared to running the method on a single GPU. This proves high scalability of the algorithm. Availability: The latest version of EBIC could be downloaded from http://github.com/EpistasisLab/ebic . Installation and usage instructions are also available online.

This article is from Big Technology, a newsletter by Alex Kantrowitz. As soon as artificial intelligence began to read, write, and code, all manner of professions were supposed to automate--fast. And yet, eight months after the release of ChatGPT--and several years since the advent of other A.I. business tools--the fallout's been muted. A.I. is being widely adopted, but the imagined mass firings haven't materialized. The United States is still effectively at full employment, with just 3.5 percent of the workforce unemployed. The usual narrative may say otherwise, but the path toward A.I.–driven mass unemployment isn't simple.

Artificial Intelligence (AI) is already being used in advanced medical settings and it has multiple applications including, wearable technology, precision medicine and virtual clinics. In some cases, it can even interpret test results more accurately than physicians. While most of us are just beginning to realise the full potential of AI, some entrepreneurs are way ahead. But how can they build trust with investors, what are the barriers for European startups and how can smaller companies get ahead? Pascal Lardier, VP for International Events and Media Content at HIMSS moderated the session around'AI Beyond the Buzz' at the HIMSS & Health 2.0 European Digital Conference, with the panel consisting of Neha Tanna, Investment Partner, Joyance Partners, Jorge Juan Fernández García, Director of Innovation, EIT Health, and Piotr Orzechowski, Founder & CEO, Infermedica in Poland.

Digital health startup Infermedica today nabbed $10.25 million to further develop its platform for symptom diagnosis. The company, which claims to have performed more than 6 million health checks to date, says it will put the proceeds toward R&D and international expansion in the U.S. and Germany. The demand for triaging solutions has risen substantially as the coronavirus pandemic rages on. Millions of patients wait at least two hours to see a provider, according to a study published by the U.S. Centers for Disease Control and Prevention (CDC). In response, tech giants including IBM, Facebook, and Microsoft have partnered with governments and private industry to roll out chatbot-based solutions, as have a number of startups.