Getting a quick and accurate reading of an X-ray or some other medical images can be vital to a patient's health and might even save a life. Obtaining such an assessment depends on the availability of a skilled radiologist and, consequently, a rapid response is not always possible. For that reason, says Ruizhi "Ray" Liao, a postdoc and a recent PhD graduate at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), "we want to train machines that are capable of reproducing what radiologists do every day." Liao is first author of a new paper, written with other researchers at MIT and Boston-area hospitals, that is being presented this fall at MICCAI 2021, an international conference on medical image computing. Although the idea of utilizing computers to interpret images is not new, the MIT-led group is drawing on an underused resource--the vast body of radiology reports that accompany medical images, written by radiologists in routine clinical practice--to improve the interpretive abilities of machine learning algorithms.
Scientists have developed a tiny 3D-printed microneedle vaccine patch that could offer a pain-free alternative to needles. In trials on mice, it offered a 10-fold greater immune response and a 50-fold greater T-cell and antigen-specific antibody response compared with a needle in the arm. The polymer patch, which is smaller than a 5p coin, needs lower doses and could be mailed to people's homes and self-administered, eliminating the need for trained medical personnel. It also offers an'anxiety-free' vaccination option for people who have a'needle phobia', also known as trypanophobia, which is putting some off getting their Covid jabs. The researchers are yet to conduct clinical trials of the patch on humans, which could pave the way for a new way of administering vaccines in the future.
Breast cancer is the second most common cancer among women in the United States; as of January 2021, there are more than 3.8 million women with a history of breast cancer in the United States. Doctors often use ultrasound, mammograms, MRI, or biopsy to find or diagnose breast cancer. In a new study, researchers from NYU and NYU Abu Dhabi (NYUAD) report that they have developed a novel artificial intelligence (AI) system that achieves radiologist-level accuracy in identifying breast cancer in ultrasound images. Their findings are published in the journal Nature Communications, in a paper titled, "Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams," and was led by Farah Shamout, PhD, NYUAD assistant professor emerging scholar of computer engineering and colleagues. "Though consistently shown to detect mammographically occult cancers, breast ultrasound has been noted to have high false-positive rates, the researchers wrote. "In this work, we present an AI system that achieves radiologist-level accuracy in identifying breast cancer in ultrasound images." "The AI system was developed and evaluated using the NYU Breast Ultrasound Dataset41 consisting of 5,442,907 images within 288,767 breast exams (including both screening and diagnostic exams) collected from 143,203 patients examined between 2012 and 2019 at NYU Langone Health in New York," noted the researchers. The primary goal of the AI system is to reduce the frequency of false-positive findings. It can detect cancer by assigning a probability for malignancy and highlight parts of ultrasound images that are associated with its predictions. When the researchers conducted a reader study to compare its diagnostic accuracy with board-certified breast radiologists, the system achieved higher accuracy than the ten radiologists on average. However, a hybrid model that aggregated the predictions of the AI system and radiologists achieved the best results in accurately detecting cancer in patients. "Our findings highlight the potential of AI to improve the accuracy, consistency, and efficiency of breast ultrasound diagnosis," explained Shamout. "Importantly, AI is not a replacement for the expertise of clinicians.
Plain Complex is a Finnish startup company founded in 2021, although the initial product development started already three years ago. As an anesthesiologist Sasu Liuhanen repeatedly witnessed the challenges of planning nurses’ shifts in his daily work; the process was slow, required a lot of manual work and the quality of the rosters left all too often a lot to desire.To develop a solution to the problem, Sasu Liuhanen, an experienced anesthesiologist and software developer, Tuomo Peltola, a seasoned professional in health-tech sales and marketing, and Stefano Campadello, a professional in business development and information technology founded a company and are now commercializing its artificial intelligence-based roster planning software. 150k from Finnish angel investors The first angel investment round of the company was completed with four renowned angel investors. Ali Omar (FiBAN business angel of the year 2019), Reima Linnanvirta (chair of the board, FiBAN), Henry Nilert (founder of IoBox, FiBAN angel investor), and Pekka Ylitalo (Dimerent) made a 150 000 € seed investment into the company. - Roster planning affects a great number of nurses and their families. Hence, the quality of the rosters has an immense effect on employees’ work-life balance and their well-being. Artificial intelligence is a true game-changer and enables finding optimal shifts for each employee, says Ali Omar. - Well-being employees are the focus of Plain Complex, but at the same time, an organization can achieve significant cost savings brought by the uniform quality and fairness of the rosters. Using artificial intelligence is a true win-win, says FiBAN’s chair of the board, Reima Linnanvirta. Artificial intelligence improves well-being at work and brings costs savings to healthcare An ongoing pilot in a large Finnish hospital has already proven that artificial intelligence can plan rosters where employees can combine shift work and personal life in a way that has not been possible before. Transforming the previously long and tedious planning process from days or even weeks into a few minutes opens up new and unseen opportunities. - A good roster needs to comply with all applicable laws, collective agreements, organizational requirements, criteria for ergonomic design, and the employees’ personal wishes and preferences. Such a puzzle is often extremely difficult to solve and frequently it is the employees’ wishes that need to give in. Artificial intelligence can change all this and solve the puzzle in a way that everyone wins. A plan that takes all the aforementioned aspects into account is ready in minutes, says Sasu Liuhanen, CEO and co-founder of the company. More information: Sasu LiuhanenCEO, Co-Founder, Plain Complex040-516 email@example.com / linkedin.com/company/plaincomplex Antti ViitanenDeal Flow Manager, FiBAN+358 45 2565 firstname.lastname@example.org
Artificial Intelligence (AI) for social good is a field of work which, broadly speaking, uses AI to make the world a better place. I had a chance to interview two leaders in the field, Dr. Bryan Wilder, who recently received his Ph.D. from Harvard (and will be joining the faculty at Carnegie Mellon next fall) and current Harvard Ph.D. student, Lily Xu. Both Bryan and Lily have been advised by Dr. Tambe, Gordon McKay Professor of Computer Science and Director of the Center for Research in Computation and Society (CRCS) at Harvard University and Director of AI for Social Good at Google Research India. While Bryan and Lily are both working at the intersection of AI and social good, they arrived at this junction via different paths. Bryan was studying computer science and looking for a field to apply his knowledge; his search led him to public health.
For years now, artificial intelligence has been hailed as both a savior and a destroyer. The technology really can make our lives easier, letting us summon our phones with a "Hey, Siri" and (more importantly) assisting doctors on the operating table. But as any science-fiction reader knows, AI is not an unmitigated good: It can be prone to the same racial biases as humans are, and, as is the case with self-driving cars, it can be forced to make murky split-second decisions that determine who lives and who dies. Like it or not, AI is only going to become an even more omnipresent force: We're in a "watershed moment" for the technology, says Eric Schmidt, the former Google CEO. Schmidt is a longtime fixture in a tech industry that seems to constantly be in a state of upheaval. He was the first software manager at Sun Microsystems, in the 1980s, and the CEO of the former software giant Novell in the '90s. He joined Google as CEO in 2001, then was the company's executive chairman from 2011 until 2017. Since leaving Google, Schmidt has made AI his focus: In 2018, he wrote in The Atlantic about the need to prepare for the AI boom, along with his co-authors Henry Kissinger, the former secretary of state, and the MIT dean Daniel Huttenlocher. The trio have followed up that story with The Age of AI, a book about how AI will transform how we experience the world, coming out in November.
Computer science degrees qualify you for some of the most in-demand tech careers in design and development, analysis, and management. As many of the largest industries integrate more complex technologies, the number of jobs for computer science majors increases. Graduates can find computer science careers in healthcare, manufacturing, business, and the government. The Bureau of Labor Statistics (BLS) projects 13% growth in computer occupations 2020-30, resulting from demands for improved technologies, security, cloud computing infrastructure, and big data applications. These professionals develop new and exciting ways to use technology, such as enhancing revenues, product quality, and health outcomes.
Our system is an interface between the position of the medical imaging device (the c-arm), image acquition parameters, and processing of the angiographic parametric imaging. The software surveys tissue perfusion in automatically placed regions of interest after each angiogram, compares it to baseline, and detects the location of ischemia with a 90% probability for accurate diagnosis. QAS.AI software has been trained on thousands of patient data. In only 15ms, QAS.AI modules can accurately locate the diseased lesion and predict treatment outcome.
In media news today, 'The View' co-host Ana Navarro reveals her COVID tests were false positives, CNN anchor Chris Cuomo stays silent on his own sexual harassment scandal, and The New Yorker hosts a climate change extremist who promotes property damage Meghan McCain spent years irking liberals as the token conservative on "The View," but managed to continue bothering the left on Sunday simply by showing up on NBC's "Meet the Press." McCain walked away from "The View" last month because she enjoyed settling down in Washington, D.C. with her family since the coronavirus pandemic and didn't want to upend her life again for the New York-based program. Meghan McCain irked liberals by appearing on NBC's "Meet the Press." Former CNN anchor Soledad O'Brien responded to video of Todd welcoming McCain to the program with a tweet that scolded "Meet the Press" for offering her a platform. "This young lady is not her father (though she likes to name him frequently). She lies on camera, she has zero value as a guest, certainly she's go no credibility as a political talking head. And yet, Meet the Press fails by allowing her to lie on their air," O'Brien tweeted.
The end of June saw the announcement that Peter Thomas would be stepping into the chief clinical information officer (CCIO) role at Moorfields Eye Hospital NHS Foundation Trust in August. The consultant joined the trust in 2017 and took a special interest in machine learning and artificial intelligence, pioneering the hospital's use of digital medicine and telemedicine. In his capacity as CCIO, Thomas will be in charge of raising awareness of clinical informatics as an important element in safe, high-quality patient care. He said: "I am delighted to be offered the role of chief clinical information officer at Moorfields and I hope to use this opportunity to use digital medicine in innovative ways to help our patients receive the best care possible." University Hospitals of Leicester NHS Trust has announced Richard Mitchell will take up the position as the trust's chief executive from Autumn 2021.