Archive 19.08.2024

A collaborative approach to automation offers solutions where older methods have fallen short. Manufacturers who have struggled to achieve desired results from conventional robotics should consider how cobots can help them strike an ideal balance.

RobotWritersAI.com is playing hooky.

We’ll be back Sept. 2, 2024 with fresh news and analysis on the latest in AI-generated writing.

The post Gone Fishin’ appeared first on Robot Writers AI.

In recent years, roboticists worldwide have designed various robotic grippers that can pick up and manipulate different types of objects. The grippers that are most effective in tackling real-world manual tasks, particularly complex object manipulation tasks, are often those inspired by human hands.

A zinc-air microbattery could enable the deployment of cell-sized, autonomous robots for drug delivery within in the human body, as well as other applications such as locating leaks in gas pipelines.

Researchers have made groundbreaking advancements in the field of soft robotics by developing film-balloon (FiBa) soft robots. These innovative robots, designed by a team led by Dr. Terry Ching and corresponding author Professor Michinao Hashimoto, introduce a novel fabrication approach that enables lightweight, untethered operation with advanced biomimetic locomotion capabilities.

The great strength of Ensenso B lies in the very precise detection of objects at close range. It provides a wide field of view and an impressively high depth of field.

A tiny battery designed by MIT engineers could enable the deployment of cell-sized, autonomous robots for drug delivery within in the human body, as well as other applications such as locating leaks in gas pipelines.

A new algorithm may make robots safer by making them more aware of human inattentiveness. In computerized simulations of packaging and assembly lines where humans and robots work together, the algorithm developed to account for human carelessness improved safety by about a maximum of 80% and efficiency by about a maximum of 38% compared to existing methods.

A new algorithm may make robots safer by making them more aware of human inattentiveness. In computerized simulations of packaging and assembly lines where humans and robots work together, the algorithm developed to account for human carelessness improved safety by about a maximum of 80% and efficiency by about a maximum of 38% compared to existing methods.

A team of engineers from several institutions in South Korea has developed a type of wheel with spokes that can be adjusted in real time to conform the wheel's shape to uneven terrain. In their paper published in the journal Science Robotics, the group describes the principles behind their wheel design and how well it worked in two- and four-wheeled test models.

GMSL2 comprises sets of serializer and deserializers (SerDes) ICs. It can provide multi-stream support with a single cable. This interface addresses the needs of high bandwidth, complex interconnect, data integrity, and low power requirements.

Large language models (LLMs), such as OpenAI's ChatGPT, are known to be highly effective in answering a wide range of user queries, generalizing well across many natural language processing (NLP) tasks. Recently, some studies have also been exploring the potential of these models for detecting and mitigating robotic system failures.

A new, air-powered computer sets off alarms when certain medical devices fail. The invention is a more reliable and lower-cost way to help prevent blood clots and strokes -- all without electronic sensors.

Advanced robot lawn mowers may leverage high-precision RTK and VSLAM technology to navigate complex landscapes with unprecedented accuracy. These systems could provide real-time adjustments to mowing patterns based on immediate environmental feedback.

This blog is a contribution from our customer University Medical Centre Mannheim, a leading university hospital in Europe. Learn how their team leverages DataRobot to accelerate clinical research with AI.

As physicians and researchers, we’re constantly working to improve quality of life. To do so, we need a holistic, data-driven approach that helps us understand the full impact of a particular treatment. How does a certain treatment impact patient symptoms? What makes their symptoms better or worse?

At University Medical Centre Mannheim, we’re digging into data to answer these questions. But it’s tough for our small teams to balance research with the critically important treatment of our patients. We don’t learn data science in medical school, but it’s an increasingly essential piece of the healthcare puzzle.

Fortunately, user-friendly AI platforms like DataRobot are helping us bridge the gaps between our medical expertise and the data science we need to provide more thoughtful care to our patients. 

The Benefits of AI in Healthcare: Findings We Can Trust

What excites me most about AI in healthcare is the potential to uncover new explanations for diseases or breakthrough therapy efficacies that we’re too blind to see using classical statistical methods. Our goal is to uncover new influences on disease progression, predict disease flares, and empower patients to better manage their treatment adherence.

DataRobot gives us exciting new ways to gain insights from our data and augment our team without data scientists. 

As clinicians, we can compare and validate models to find those with the highest degree of accuracy. In the Clinical Cooperation Unit – Healthy Skin and Joints, we’ve leveraged AI to evaluate data from a smartphone app, including images and other clinical datasets of anonymized patient data.

Compliance is also critical — from privacy measures around patient information to GDPR regulations that protect and secure sensitive data. When we publish our findings, the most important thing is their reproducibility. That’s why documentation and explainability behind models are so critical. DataRobot makes these normally labor-intensive processes seamless and automatic. 

With DataRobot, we trust our findings, knowing that they have been thoroughly trained, retrained, validated, and revalidated. We have a plethora of statistics to show the level of accuracy, which we also need for publishing results. Because of that, I sleep better at night and our centre can make an even greater contribution to the medical research community.

Uncovering Links in Disease Progression

Another example of AI being used in healthcare: we’ve applied AI to several use cases in our dermatology and rheumatology collaboration. 

For a recently published study, we used DataRobot to analyze data from clinical research with patients with chronic eczema or psoriasis. The analysis focused on itching, pain, quality of life, and the use of a smartphone monitoring app to track their symptoms. We looked at uncovering new influences on disease progression, trying to predict disease flares or promote patient treatment adherence.

Through our analysis, we learned that nearly 30% of patients see improved quality of life at six months, while another 30% either showed a decline in quality of life or had consistently poor quality of life. Those insights and others will influence treatment decisions. This data is transformative because we can better understand our patients and learn which patients benefit from certain therapies. It informs us on when and how to change patients’ course of treatment if needed.

Now we’re helping other clinics in the medical center uncover insights in their data. With the Department of Internal Medicine, we’ve looked at blood lipids with the goal of predicting heart disease or heart attacks. In just a few weeks/months, we’ve been able to create some pretty accurate models and look forward to publishing our findings in the near future.

Using AI to Accelerate Medical Research

All these findings may have gone undiscovered without DataRobot. Instead, we’ve been able to accelerate research from hours to seconds, even as we continue to see patients and focus on improving their quality of life

AI helps our daily work, and most importantly, it helps patients.

When we first partnered with DataRobot, I told others that this new technology would change the face of the Earth and that they had to learn about it. I’m still saying this today. AI offers enormous benefits to healthcare professionals, and I’m thrilled to see the impact of University Medical Centre Mannheim’s work.

The post Customer Spotlight: How Doctors and Researchers Optimize Patient Outcomes with AI appeared first on DataRobot.