February 23, 2024

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U.S. Researchers Machine Learning System Flags Treatment that Might Do More Harm Than Good

Sepsis claims the lives of nearly 270,000 people in the U.S. each year. An unpredictable illness can progress quickly, resulting in a speedy drop in blood strain, tissue injury, several organ failures, and demise. Well-timed intervention by healthcare professionals saves lives, however some therapies for sepsis can even worsen an affected person’s situation, so selecting the very best remedy may be difficult. For instance, within the early hours of extreme sepsis, giving an excessive amount of intravenous fluid can improve the affected person’s threat of demise.

To help clinicians avoid remedies that may potentially contribute to a patient’s death, researchers at MIT have developed a machine learning model that could be used to identify treatments that pose a higher risk than other options. Their model can also warn doctors when a septic patient is approaching a medical dead end — the point when the patient will most likely die no matter what treatment is used — so that they can intervene before it is too late.

When utilised to a dataset of sepsis sufferers in a hospital intensive care unit, the investigator mannequin confirmed that about 12% of the therapies for deceased sufferers have been dangerous. The research additionally exhibits that about 3 p.c of sufferers who didn’t survive have been caught in a medical stalemate 48 hours earlier than demise.

“We see that our model is almost eight hours ahead of a doctor’s recognition of a patient’s deterioration. This is powerful because in these really sensitive situations, every minute counts, and being aware of how the patient is evolving, and the risk of administering certain treatment at any given time, is really important.”

Taylor Killian, a graduate student in the Healthy ML group of the Computer Science and Artificial Intelligence Laboratory (CSAIL).

This research project was spurred by a paper that explored the usage of reinforcement studying in conditions the place it is too harmful to analyse voluntary actions, making it tough to generate sufficient information to successfully practice algorithms. Conditions the place it is not potential to gather extra information forward of time are known as “offline” settings.

In reinforcement learning, the algorithm is trained through trial and error and learns to take actions that maximise its accumulation of reward. But in a health care setting, it is nearly impossible to generate enough data for these models to learn the optimal treatment, since it isn’t ethical to experiment with possible treatment strategies.

So, the researchers flipped reinforcement learning on its head. They used the limited data from a hospital ICU to train a reinforcement learning model to identify treatments to avoid, with the goal of keeping a patient from entering a medical dead end. Learning what to avoid is a more statistically efficient approach that requires less data.

The researchers also found that 20% to 40% of patients who did not survive raised at least one yellow flag prior to their death, and many raised that flag at least 48 hours before they died. The results also showed that, when comparing the trends of patients who survived versus patients who died, once a patient raises their first flag, there is a very sharp deviation in the value of administered treatments. The window of time around the first flag is a critical point when making treatment decisions.

Moving forward, the researchers also want to estimate causal relationships between treatment decisions and the evolution of patient health. They plan to continue enhancing the model so it can create uncertainty estimates around treatment values that would help doctors make more informed decisions. Another way to provide further validation of the model would be to apply it to data from other hospitals, which they hope to do in the future.

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Qlik’s vision is a data-literate world, where everyone can use data and analytics to improve decision-making and solve their most challenging problems. A private company, Qlik offers real-time data integration and analytics solutions, powered by Qlik Cloud, to close the gaps between data, insights and action. By transforming data into Active Intelligence, businesses can drive better decisions, improve revenue and profitability, and optimize customer relationships. Qlik serves more than 38,000 active customers in over 100 countries.

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CTC Global Singapore, a premier end-to-end IT solutions provider, is a fully owned subsidiary of ITOCHU Techno-Solutions Corporation (CTC) and ITOCHU Corporation.

Since 1972, CTC has established itself as one of the country’s top IT solutions providers. With 50 years of experience, headed by an experienced management team and staffed by over 200 qualified IT professionals, we support organizations with integrated IT solutions expertise in Autonomous IT, Cyber Security, Digital Transformation, Enterprise Cloud Infrastructure, Workplace Modernization and Professional Services.

Well-known for our strengths in system integration and consultation, CTC Global proves to be the preferred IT outsourcing destination for organizations all over Singapore today.

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Planview has one mission: to build the future of connected work. Our solutions enable organizations to connect the business from ideas to impact, empowering companies to accelerate the achievement of what matters most. Planview’s full spectrum of Portfolio Management and Work Management solutions creates an organizational focus on the strategic outcomes that matter and empowers teams to deliver their best work, no matter how they work. The comprehensive Planview platform and enterprise success model enables customers to deliver innovative, competitive products, services, and customer experiences. Headquartered in Austin, Texas, with locations around the world, Planview has more than 1,300 employees supporting 4,500 customers and 2.6 million users worldwide. For more information, visit www.planview.com.

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SIRIM is a premier industrial research and technology organisation in Malaysia, wholly-owned by the Minister​ of Finance Incorporated. With over forty years of experience and expertise, SIRIM is mandated as the machinery for research and technology development, and the national champion of quality. SIRIM has always played a major role in the development of the country’s private sector. By tapping into our expertise and knowledge base, we focus on developing new technologies and improvements in the manufacturing, technology and services sectors. We nurture Small Medium Enterprises (SME) growth with solutions for technology penetration and upgrading, making it an ideal technology partner for SMEs.

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HashiCorp provides infrastructure automation software for multi-cloud environments, enabling enterprises to unlock a common cloud operating model to provision, secure, connect, and run any application on any infrastructure. HashiCorp tools allow organizations to deliver applications faster by helping enterprises transition from manual processes and ITIL practices to self-service automation and DevOps practices. 

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IBM is a leading global hybrid cloud and AI, and business services provider. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Nearly 3,000 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM’s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and business services deliver open and flexible options to our clients. All of this is backed by IBM’s legendary commitment to trust, transparency, responsibility, inclusivity and service.

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