One of the Companies, Shahed Aviation Industries Research Center , Has Designed and ... - Latest Tweet by The Kyiv Independent

 

The latest Tweet by The Kyiv Independent states, 'One of the companies, Shahid Aviation Industries Research Center, has designed and manufactured several Shahid-series drones, including the Shahid-136 one-way attack UAV that Russian forces have used in recent attacks targeting civilian infrastructure across Ukraine.'

" One of the companies, Shahed Aviation Industries Research Center (SAIRC), has designed and manufactured several Shahed-series drones, including the Shahed-136 one-way attack UAV that Russian forces have used in recent attacks targeting civilian infrastructure across Ukraine."

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Study finds the risks of sharing health care data are low

Greater availability of de-identified patient health data would enable better treatments and diagnostics, the researchers say.

In recent years, scientists have made great strides in their ability to develop artificial intelligence algorithms that can analyze patient data and come up with new ways to diagnose disease or predict which treatments work best for different patients.

The success of those algorithms depends on access to patient health data, which has been stripped of personal information that could be used to identify individuals from the dataset. However, the possibility that individuals could be identified through other means has raised concerns among privacy advocates.

In a new study, a team of researchers led by MIT Principal Research Scientist Leo Anthony Celi has quantified the potential risk of this kind of patient re-identification and found that it is currently extremely low relative to the risk of data breach. In fact, between 2016 and 2021, the period examined in the study, there were no reports of patient re-identification through publicly available health data.

The findings suggest that the potential risk to patient privacy is greatly outweighed by the gains for patients, who benefit from better diagnosis and treatment, says Celi. He hopes that in the near future, these datasets will become more widely available and include a more diverse group of patients.

“We agree that there is some risk to patient privacy, but there is also a risk of not sharing data,” he says. “There is harm when data is not shared, and that needs to be factored into the equation.”


Celi, who is also an instructor at the Harvard T.H. Chan School of Public Health and an attending physician with the Division of Pulmonary, Critical Care and Sleep Medicine at the Beth Israel Deaconess Medical Center, is the senior author of the new study. Kenneth Seastedt, a thoracic surgery fellow at Beth Israel Deaconess Medical Center, is the lead author of the paper, which appears today in PLOS Digital Health.

Risk-benefit analysis

Large health record databases created by hospitals and other institutions contain a wealth of information on diseases such as heart disease, cancer, macular degeneration, and Covid-19, which researchers use to try to discover new ways to diagnose and treat disease.

Celi and others at MIT’s Laboratory for Computational Physiology have created several publicly available databases, including the Medical Information Mart for Intensive Care (MIMIC), which they recently used to develop algorithms that can help doctors make better medical decisions. Many other research groups have also used the data, and others have created similar databases in countries around the world.

Typically, when patient data is entered into this kind of database, certain types of identifying information are removed, including patients’ names, addresses, and phone numbers. This is intended to prevent patients from being re-identified and having information about their medical conditions made public.

However, concerns about privacy have slowed the development of more publicly available databases with this kind of information, Celi says. In the new study, he and his colleagues set out to ask what the actual risk of patient re-identification is. First, they searched PubMed, a database of scientific papers, for any reports of patient re-identification from publicly available health data, but found none.

To expand the search, the researchers then examined media reports from September 2016 to September 2021, using Media Cloud, an open-source global news database and analysis tool. In a search of more than 10,000 U.S. media publications during that time, they did not find a single instance of patient re-identification from publicly available health data.

In contrast, they found that during the same time period, health records of nearly 100 million people were stolen through data breaches of information that was supposed to be securely stored.

“Of course, it’s good to be concerned about patient privacy and the risk of re-identification, but that risk, although it’s not zero, is minuscule compared to the issue of cyber security,” Celi says.

Better representation

More widespread sharing of de-identified health data is necessary, Celi says, to help expand the representation of minority groups in the United States, who have traditionally been underrepresented in medical studies. He is also working to encourage the development of more such databases in low- and middle-income countries.

“We cannot move forward with AI unless we address the biases that lurk in our datasets,” he says. “When we have this debate over privacy, no one hears the voice of the people who are not represented. People are deciding for them that their data need to be protected and should not be shared. But they are the ones whose health is at stake; they’re the ones who would most likely benefit from data-sharing.”

Instead of asking for patient consent to share data, which he says may exacerbate the exclusion of many people who are now underrepresented in publicly available health data, Celi recommends enhancing the existing safeguards that are in place to protect such datasets. One new strategy that he and his colleagues have begun using is to share the data in a way that it can’t be downloaded, and all queries run on it can be monitored by the administrators of the database. This allows them to flag any user inquiry that seems like it might not be for legitimate research purposes, Celi says.

“What we are advocating for is performing data analysis in a very secure environment so that we weed out any nefarious players trying to use the data for some other reasons apart from improving population health,” he says. “We’re not saying that we should disregard patient privacy. What we’re saying is that we have to also balance that with the value of data sharing.”

The research was funded by the National Institutes of Health through the National Institute of Biomedical Imaging and Bioengineering.

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ROUX INSTITUTE RESEARCHER TO CAPTURE REAL-TIME DATA FROM ICU MONITORS FOR BETTER PATIENT OUTCOMES

Bedside monitors in cardiac intensive care units measure everything from patients’ blood pressure and blood oxygen levels to their heart rate and rhythm.



The numerical and waveform measurements provide valuable information for doctors and nurses monitoring patients for immediate signs of distress. But once that information flashes across a screen, it is gone forever.

What if the data could be captured and crunched in real time?Could big data help predict which patients might be susceptible to infections that could lead to potentially deadly sepsis?

Could it identify patients who are at heightened risk for readmission?

Raimond “Rai” Winslow, a national leader in computational medicine based at Northeastern’s Roux Institute in Portland, Maine, thinks so.

He is a principal investigator in a research project being conducted with MaineHealth that aims to take complex data sets about patients in the state’s largest cardiothoracic ICU and translate them into metrics that could better predict adverse outcomes—in time for physicians to avert them whenever possible.

The project is known as HEART for Healthcare Enabled by AI in Real-Time and is funded in large part by Northeastern University’s Impact Engine program.

“The goal of HEART is to use machine learning models to collect data from patients while they are recovering in the CT ICU, and at every moment of time a new measurement comes in to predict their risk for developing a complication,” says Winslow, director of Life Science and Medicine Research at the Roux.

Twenty percent of cardiac surgical patients develop complications, and of those patients, 20% do not survive, he says.

Physicians can use the level of risk assigned to patients by computational medicine to determine which patients need more intense treatment and which are doing fine, he says.

“The idea being that if you can make this prediction in advance before the complication has actually occurred you can intervene and help with it.”

Winslow says he started working on the HEART project about a year ago, after coming to the Roux Institute from the Johns Hopkins University School of Medicine, where he was the founding director of the Institute for Computational Medicine.

Dr. Douglas Sawyer, chief academic officer at MaineHealth and the Maine Medical Center, posed the project to him, and “it’s moved quickly,” Winslow says.

He says he expects to enroll recovering cardiac surgery patients in MaineHealth’s 12-bed ICU in clinical trials in 18 months.But first the researchers have to develop a model of the cardiovascular disease process using large patient datasets and animal models of disease.

The next step is to take streaming data from individual patients, send it to the cloud for de-identification, and analyze what the data bodes for the patients’ recovery.

“We use machine learning methods applied to population data to learn an algorithm that could reliably select patients with sepsis who are going to develop septic shock,” for instance, Winslow says.

If the estimation of developing the often-fatal syndrome is 90%, physicians likely will take a different approach than if the risk for a particular patient is 20%, he says.

The final step is to find a way to deliver the information to medical staff in a digestible, timely format, Winslow says.

“We don’t tell (physicians) what to do, what interventions to take,” he says. “We’re simply notifying them that that patient is headed toward a complication. ‘Use your knowledge and your savvy and your intuition and your experience to treat that patient as you see fit.’”

Winslow predicts the HEART project will help reduce readmissions by helping patients recover more fully in the hospital.

for more info : https://news.northeastern.edu/2022/10/11/heart-research-icu-data/

News from the world of Education:

Pune Knowledge Cluster (PKC), in collaboration with Lenovo, recently launched the ‘Teach with Tech’ programme for school students and teachers in Maharashtra. It aims to provide an opportunity for students and teachers to access and adopt digital content related to Science, Maths, and Technology.



M.Sc Stem Cell and Regenerative Medicine

The University of Sheffield, the U.K., invites applications for its M.Sc Stem Cell and Regenerative Medicine course starting in September 2023.

Eligibility: A three-or-four-year Bachelor’s degree from a recognised university in a Biomedical-related subject. Overall IELTS score of 6.5 with a minimum of 6.0 in each component, or equivalent, is required.

The university’s students have raised over £85,000, and dedicated 33,000 hours volunteering in the local community, in the past year.

MRes Physics

The University of Strathclyde, Glasgow, invites applications for its MRes Physics course starting in January 2023.

Eligibility: First-class or upper second-class (2:1) UK Honours degree, or overseas equivalent, in physics or a related subject, from a recognised educational establishment. IELTS minimum score of 6.5 (with no component below 6.0)

For details, visit, https://bit.ly/3SNADk2

M.Sc. Advanced Mechanical Engineering with Aerospace

The University of Strathclyde, Glasgow, invites applications for its M.Sc. Advanced Mechanical Engineering with Aerospace course starting in January 2023. Scholarships are available.

Eligibility: A first-class or second-class honours degree (or international equivalent) in Engineering or Physical Sciences, or equivalent professional qualification is required; a lower-class degree may be considered with relevant work experience. IELTS (Academic): 6.5 overall (no individual band less than 5.5).

For other details, visit, https://bit.ly/3Vhn6Tt

PG Cert Global Mental Health and Wellbeing

The University of Essex Online invites applications for the October intake of its online PG Cert Global Mental Health and Wellbeing.

Eligibility: For the academic entry route, students must have an undergraduate degree from an approved institution, equivalent to a U.K. Honours degree, or a relevant professional qualification. For the work experience entry route, students must have at least three years of work experience (voluntary or paid) within a relevant field, supported by two appropriate references. Applicants have to undergo an aptitude test. English language ability should be equivalent to IELTS Academic score of 6.5.

Deadline: October 20

Apply at https://online.essex.ac.uk/apply/

PGDM admissions open

Goa Institute of Management has opened admissions for its two-year residential PGDM Programmes in in Core Management, Healthcare Analytics, Big Data Analytics, and Banking, Insurance and Financial Services.

Eligibility: Performance in competitive exams such as the XAT, CAT, GMAT, or CMAT. Personal interviews, work experience, and previous academic records will be considered in the final round.

Deadline: November 15 for early round. Two more rounds will be held in December before the final call for applications in early January 2023.

To apply, visit, www.gim.ac.in

Masters in DevOps for IT graduates

Xebia Academy recently launched Masters in DevOps for IT graduates. For details, and to apply, visit, https://www.xebiaacademyglobal.com/course/careerpro/master-programs/devops

Sustainability and ESG Courses for the Fashion and Textile Sector

Sasmira’s Institute of Design and Textiles (SIDT) and The Academy for Sustainability (TAS) recently announced a collaboration to launch various courses on Sustainability for the Fashion and Textile Sector. They have launched a series of programmes, ranging from training through Certificate and Diploma programmes to various tailor-made corporate training programmes.

PGDM and PGDM (BM) programmes

Bharatiya Vidya Bhavan’s S.P. Jain Institute of Management and Research (SPJIMR) recently opened admissions to Post Graduate Diploma in Management (PGDM) programme, and a Post Graduate Diploma in Management-Business Management (PGDM-BM) programme, two-year, full-time residential programmes.

Eligibility: Bachelor's degree or equivalent in any discipline from a recognised university; students in their final year of graduation can also apply. Scores of CAT 2022 or GMAT (Jan 2020 onwards); Work experience is not mandatory

Deadline: November 25

To apply, visit, https://pgdmadmissions.spjimr.org/spjimr-2023-25

New PG courses at Macquarie University

Macquarie University recently introduced two new postgraduate courses — Master of Information Technology in Artificial Intelligence (only applicable to students with prior experience in fields such as Information Technology, Statistics, Maths, Engineering, Science, Actuarial Studies, Data Science, Statistics, and Computing) and Master of Information Technology in Internet of Things (students from Cybersecurity, Computer Security, Information Technology, Computer Science Software Engineering, Network Engineering, Telecommunications Engineering can apply), slated to begin in 2023.

Admission: The applications for the February and July 2023 intakes are now open

Those interested, apply at, https://bit.ly/3RQaFv1

Research conducted by psychologists from the university’s mental health service, MindSpot, found five behavioural traits to good mental health — meaningful activity, healthy thinking, having goals and making plans, healthy routines, and, social connections.

University of Dundee scholarship for Indian students

The University recently announced that its Vice-Chancellor’s Scholarships for South Asia (https://bit.ly/3EuXpZK) will be offered to applicants from any South Asian country — Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, Sri Lanka.

Eligibility: The scholarship is available for all undergraduate applicants for entry in September 2023with the exception of those applying for Medicine and Dentistry, and all taught postgraduate applicants for entry in September 2023 or January 2024.

Other scholarships, from the university’s scholarship fund, are also available for undergraduate and postgraduate students from India, including the Global Citizenship Scholarship (https://bit.ly/3fQp6SB), the Global Excellence Scholarship (https://bit.ly/3fXSmXK), and the JaintiDass Saggar Memorial Scholarship for Excellence (https://bit.ly/3EyWcka) worth £5,000.

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Top 10 books can provide information to the data storage architects who have an interest in Data Storage.

 

Data storage architects are entrusted with a great deal of responsibility. It is important to be able to manage huge volumes of data without issue. Books are a fantastic source for experts wanting to learn about a certain sector of technology, whether hardback or digital, and data storage architects are no exception. Here is a list of the top ten books for data storage architects. These books are prepared by writers with expertise and renown in data storage and are designed for both beginners and specialists.

1. The Artificial Intelligence Infrastructure Workshop

2. MongoDB: The Definitive Guide

3. Principles of Database Management

4. Software-Defined Data Infrastructure Essentials

5. The Data Warehouse Toolkit

6. Data Center Storage

7. The Enterprise Big Data Lake

8. The History of Data Storage

9. Information Storage and Management

10. Computer Engineering, Data Storage, Networking and Security

details : 

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Big Data Analytics Tutorial

 The volume of data that one has to deal with has exploded to unimaginable levels in the past decade, and at the same time, the price of data storage has systematically reduced. Private companies and research institutions capture terabytes of data about their users’ interactions, business, social media, and also sensors from devices such as mobile phones and automobiles. The challenge of this era is to make sense of this sea of data. This is where big data analytics comes into the picture.

Big Data Analytics largely involves collecting data from different sources, munge it in a way that it becomes available to be consumed by analysts, and finally deliver data products useful to the organization business.

The process of converting large amounts of unstructured raw data, retrieved from different sources to a data product useful for organizations forms the core of Big Data Analytics.

In this tutorial, we will discuss the most fundamental concepts and methods of Big Data Analytics.

Topics include :

• Big Data Analytics Tutorial
• Big Data Analytics - Home
• Big Data Analytics - Overview
• Big Data Analytics - Data Life Cycle
• Big Data Analytics - Methodology
• Core Deliverables
• Key Stakeholders
• Big Data Analytics - Data Analyst
• Big Data Analytics - Data Scientist

• Big Data Analytics Project
• Data Analytics - Problem Definition
• Big Data Analytics - Data Collection
• Big Data Analytics - Cleansing data
• Big Data Analytics - Summarizing
• Big Data Analytics - Data Exploration
• Data Visualization

• Big Data Analytics Methods
• Big Data Analytics - Introduction to R
• Data Analytics - Introduction to SQL
• Big Data Analytics - Charts & Graphs
• Big Data Analytics - Data Tools
• Data Analytics - Statistical Methods

• Advanced Methods
• Machine Learning for Data Analysis
• Naive Bayes Classifier
• K-Means Clustering
• Association Rules
• Big Data Analytics - Decision Trees
• Logistic Regression
• Big Data Analytics - Time Series
• Big Data Analytics - Text Analytics
• Big Data Analytics - Online Learning

• Big Data Analytics Useful Resources
• Big Data Analytics - Quick Guide
• Big Data Analytics - Resources
• Big Data Analytics - Discussion

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7 Tips for Detecting Online Fraud

 Running an eCommerce business comes with its own unique set of challenges. One of the biggest is trying to figure out which of your customers are who they say they are and which are trying to commit fraud using stolen payment information.

Table of Content

1.     Fight fraud with Address Verification Service (AVS)
2.    Check location information for fraud indicators
3.    Google your customers
4.    Check for suspicious email addresses
5.     Detect fraud by noticing unusual account activity
6.     What are the best ways to stop fraud?
7.    How do I spot the fraud?
8.     How do I spot friendly fraud?
9. .  How is fraud most commonly detected?

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 Video: 

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Data Science vs. Data Analytics vs. Machine Learning: Expert Talk

Data science is a concept used to tackle big data and includes preparation, and analysis. A data scientist gathers data from multiple sources and applies machine learning, predictive analytics, and sentiment analysis to extract critical information from the collected data sets.

A data analyst is usually the person who can do basic descriptive statistics, visualize data, and communicate data points for conclusions. They must have a basic understanding of statistics, a perfect sense of databases, the ability to create new views, and the perception to visualize the data.

Machine learning can be defined as the practice of using algorithms to extract data, learn from it, and then forecast future trends for that topic. Traditional machine learning software is statistical analysis and predictive analysis that is used to spot patterns and catch hidden insights based on perceived data. 

Do you know more about this?

1. Data Science vs. Data Analytics

2. Data Science vs. Machine Learning

3. Enroll in Our PGP in Data Analytics, Data Science, AI and Machine Learning Today

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Top 7 Big Data Trends to Dominate 2021

 

Big data is a term that describes the large volume of data – both structured and unstructured – that updates a business on a day-to-day basis. But it's not the amount of data that's important. It's what organizations do with the data that matters.

Here are seven top big data trends organizations will need to watch to better reinforce and secure disrupted businesses. Have a look at the summary of those trends

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Quote : "No matter how carefully a project is planned, something may still go wrong with it " - Robert Burns.