Ivy’s Data Science Weekly 09032021

AIWelcome to our weekly news section where we discuss news, developments, and researches about data science, artificial intelligence (AI), machine learning that has happened in the past week.  
Researchers have developed a method based on Artificial Intelligence (AI) that rapidly identifies currently available medications that may treat Alzheimer’s disease. The method could represent a rapid and inexpensive way to repurpose existing therapies. The ones that carve their way into new treatments for this progressive, debilitating neurodegenerative condition. Importantly, it could also help reveal new, unexplored targets for therapy by pointing to mechanisms of drug action. 
It relies on machine learning in which systems are trained on vast amounts of data. They learn to identify telltale patterns and augment researchers’ and clinicians’ decision-making. The method then determines whether the changes induced by a drug correlate with molecular markers of disease severity. The approach also allowed the researchers to identify drugs that had protective as well as damaging effects on brain cells. 
India has the opportunity to significantly expand its pipeline of talent. This is possible if many more students across disciplines prepare for jobs in data science. Data scientists can come from different fields. In addition to that, data scientists solve problems across industries — from retail to education and personal finance. They come up with solutions using math, theory, with their particular choice of applied methods. It could be experimentation, causal inference, or machine learning. 
The first step is about deciding what type of data scientist one wants to become. In addition to that, it is important to know if the interest lies in the analysis (decision science) or building (data products/machine learning scientist). However, hiring managers look for a range of skills. Alongside foundational knowledge in math and statistics, preferred programming or computational skills for decision science roles include SQL, Hive, and data manipulation (for data access), besides scripting languages like R or Python (for analysis). 
The researchers have simulated a soft-bodied robot that turns rigid on demand. Such advances may help broaden robots’ range of tasks and allow for safe interactions with people, including inpatient care. “This is the first step in trying to see if we can get the best of both worlds,” says James Bern, the paper’s lead author and a postdoc in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).
He will present the research at the IEEE International Conference on Soft Robotics next month. Bern’s advisor, Daniela Rus, who is the CSAIL director and the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science, is the paper’s other author.
The researchers have succeeded in making an AI understand our subjective notions of what makes faces attractive. The device demonstrated this knowledge by its ability to create new portraits on its own that were tailored to be found personally attractive to individuals. The results can be utilized, for example, in modeling preferences and decision-making as well as potentially identifying unconscious attitudes.
The technique is based on a novel brain-computer interface. Previously, similar brain-computer interfaces have been able to perform one-way communication from brain to computer, such as spell individual letters or move a cursor.
In the era of social distancing, using robots for some health care interactions is a promising way to reduce in-person contact between health care workers and sick patients. However, a key question that needs to be answered is how patients will react to a robot entering the exam room. In a larger online survey conducted nationwide, the researchers also found that a majority of respondents were open to having robots. In addition to that, they were not only open about the assistance with patient triage but also perform minor procedures such as taking a nose swab.
Peter Chai, an assistant professor of emergency medicine at Brigham and Women’s Hospital and a research affiliate in Traverso’s lab, is the lead author of the study.

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