New software tool uses AI to identify cancer cells

A team of researchers from UT Southwestern has developed a software that employs Artificial Intelligence to recognize cancer cells from digital pathology images. The software named as ConvPath, identify cells based on their appearance in the pathology images using an AI algorithm that learns from human pathologists. The algorithm effectively converts a pathology image into a “map” that displays the three-dimensional distributions and interactions of tumor cells, stromal cells, and lymphocytes in tumor tissue. The researchers believe that such information can help doctors customize treatment plans and pinpoint the right immunotherapy.

Reference Linkhttps://medicalxpress.com/news/2019-12-software-tool-ai-doctors-cancer.html

World’s first AI University at Abu Dhabi offers 100% scholarships

Abu Dhabi has just launched the “world’s first AI university” in the city of in Masdar City known as the Mohammad Bin Zayed University of Artifical Intelligence (MBZUAI). Abu Dhabi is also one of the first nations to appoint a minister for artificial intelligence in 2017.

MBZUAI’s website mentions that “a graduate-level, research-based academic institution that offers specialized degree programs for local and international students in the field of Artificial Intelligence.” Shaikh Mohammad Bin Zayed Al Nahyan, Abu Dhabi’s crown prince tweeted “Launching of the world’s first graduate-level artificial intelligence university in Abu Dhabi echoes the UAE’s pioneering spirit, and paves the way towards a new era of innovation and technological advancement that benefits the UAE and a world.”

Reference Link: https://www.theweek.in/news/sci-tech/2019/10/16/uae-launches-worlds-first-ai-university-with-100-scholarships.html

AI peer reviewers smoothen the publishing grind

Peer review by artificial intelligence (AI) is promising to improve the process, enhance the quality of published papers — and save reviewers time. A handful of academic publishers are driving AI tools to do anything from selecting reviewers to checking statistics and summarizing a paper’s findings. In June, software called StatReviewer adopted by Aries Systems verifies the statistics and methods used in the manuscripts. ScholarOne, another peer-review platform is teaming up with UNSILO of Aarhus, Denmark, which uses natural language processing and machine learning to analyze manuscripts. UNSILO automatically pulls out key concepts to summarize what the paper is about. These tools can make sure a manuscript is up to scratch, but in no way are they replacing what a reviewer would do in terms of evaluation.

Reference Link : https://www.nature.com/articles/d41586-018-07245-9

AI and scientific literature work in sync

When scholars choose a topic to work on their research, they need more sources or materials to review literature and add more value to their findings. According to Canadian science publishing’s article from last year, 2.5 million research papers are published annually while another unidentified source suggests that new researches are published around the world; approximately 1 million each year! Which is equal to one every 30 seconds. With the overload of new papers in each field and more growing every year it is practically impossible for scholars to keep with the information that is put out in each paper. Christian Berger’s team from the University of Gothenburg in Sweden, found a staggering number of papers on the subject; more than 10,000 in the same subject. Fortunately, the team had the support of an AI system, a writing investigation tool called Iris.ai.

Iris.ai is an AI, a tool developed for scholars to make writing research papers easier. It is a Berlin-based company that claims to save 90% of time with 85% precision of data matching, has more than 70 m open access papers. Iris.ai is programmed to learn about the topic provided and perform an elaborate frequency analysis over the text. Then it read the words for which it needs to find results and additional material that could be helpful for the paper. It uses a 500-word description of the researcher’s issue, or the link of their paper and the AI restores a guide to thousands of coordinating reports. As the website suggests, it is a scientific writing assistant.

According to Berger, it was “a quick and nevertheless precise overview of what should be relevant to a certain research question”. Iris.ai is one among many of the new AI-based tools offering targeted results of the knowledge landscape. One such tool is called Semantic Scholar, produced by the Allen Institute for Artificial Intelligence in Seattle, Washington, and Microsoft Academic.

Although every instrument is different from each other and gives different output, they all provide researchers with a different look at the scientific literature than conventional tools such as PubMed and Google Scholar. Semantic Scholar is a browser-based search tool that mimics the engines like Google and it is free. But it is more informative than Google Scholar in terms of specific results required by researchers. Doug Raymond, Semantic Scholar’s general manager, says that one million individuals utilize their service every month. It uses natural language processing or NLP to extract data while building connections to determine if the information is relevant and reputable or not.

Artificial intelligence is saving a lot of time and making it easier and quicker to automate some procedures. In the academic publishing industry, the Al-based innovations are being produced and implemented to help both authors and publishers for peer reviews, searching published content, detecting plagiarism, and identifying data fabrication. AI could be costly, but it can accelerate a researchers’ access to new fields. More and more such AI tools are being developed to cater to various requisites of writing a paper, such as filtering topics for relevance, keyword search, etc.

Experts who need more assistance for their specific concerns might consider free Al­ tool such as Microsoft Academic or Semantic Scholar. While AI is easing so many burdens and saving time for a researcher, let’s not forget that it is still machine intelligence and may require human intervention here and there to make a paper more presentable and precise.