Saturday December 7, 2019

scGen- Artificial Intelligence (AI)-Powered Tool Promises to Reshape the Way We Study Diseases

According to the researchers, scGen is a generative deep learning model that leverages ideas from image

0
//
scGen, Artificial Intelligence, Disesase
The study, published in the journal Nature Methods, shows scGen will help mapping and studying cellular response to diseases and their treatment beyond experimentally available data. Pixabay

Researchers have developed — scGen — an Artificial Intelligence (AI)-powered tool which promises to reshape the way we study diseases and their treatment at cellular level.

The study, published in the journal Nature Methods, shows scGen will help mapping and studying cellular response to diseases and their treatment beyond experimentally available data.

According to the researchers, scGen is a generative deep learning model that leverages ideas from image, sequence and language processing and applies them to model the behaviour of a cell performed on computer or via computer simulation.

The next step for the team will be to improve scGen, make it a fully data-driven formulation, increasing its predictive power to enable the study of combinations of perturbations.

scGen, Artificial Intelligence, Disesase
Researchers have developed — scGen — an Artificial Intelligence (AI)-powered tool which promises to reshape the way we study diseases and their treatment at cellular level. Pixabay

“We can now start optimising scGen to answer more and more complex questions about diseases,” said the researcher Alex Wolf from the Technical University of Munich in Germany.

Large-scale atlases of organs in a healthy state are soon going to be available, in particular, within the Human Cell Atlas. This is a significant step in understanding cells, tissues and organs in healthy state in a better way and providing a reference while diagnosing, monitoring and treating diseases.

Accurately modelling cellular response to perturbations e.g. disease, compounds and genetic interventions, is a central goal of computational biology.

In addition, scGen is the first tool that predicts cellular response out-of-sample. This means that scGen, if trained on data that captures the effect of perturbations for a given system, is able to make reliable predictions for a different system.

Also Read- Cisco Ready with Sixth-Generation Wi-Fi for Faster Connectivity Compatible for Fifth-Generation Cellular Network

“For the first time, we have the opportunity to use data generated in one model system such as mouse and use the data to predict disease or therapy response in human patients,” said Mohammad Lotfollahi from Technical University of Munich. (IANS)

Next Story

AI-based Algorithm to Help Doctors Treat Traumatic Brain Injury

AI-based algorithm to treat brain injury developed

0
Artificial Intelligence brain
An AI-based algorithm will help doctors treat patients with severe traumatic brain injury (TBI). Pixabay

Researchers, including one of Indian-origin, have developed an artificial intelligence (AI) based algorithm that could help doctors treat patients with severe traumatic brain injury (TBI).

The algorithms can predict the probability of the patient dying within 30-days with an accuracy of 80-85 per cent, said the study published in the journal Scientific Reports.

“A dynamic prognostic model like this has not been presented before. Although this is a proof-of-concept and it will still take some time before we can implement algorithms like this into daily clinical practice, our study reflects how and into what direction modern intensive care is evolving”, said Indian-origin researcher and study author Rahul Raj from Helsinki University Hospital in the Finland.

Traumatic brain injury is a significant global cause of mortality and morbidity with an increasing incidence, especially in low-and-middle income countries.

The most severe TBIs are treated in intensive care units (ICU), but in spite of the proper and high-quality care, about one in three patients dies.

Brain Injury
Traumatic brain injury is a significant global cause of mortality and morbidity. Pixabay

This is why researchers at Helsinki University Hospital (HUS) started to develop an artificial intelligence (AI) based algorithm that could help doctors treat patients with severe TBI.

At its best, such an algorithm could predict the outcome of the individual patient and give objective data regarding the condition and prognosis of the patient and how it changes during treatment.

“We have developed two separate algorithms. The first algorithm is simpler and is based only upon objective monitor data. The second algorithm is slightly more complex and includes data regarding the level of consciousness, measured by the widely used Glasgow Coma Scale score,” said study researcher Eetu Pursiainen.

As expected, the accuracy of the more complex algorithm is slightly better than for the simpler algorithm.

Also Read- Air Pollution Identified as a Life-threatening Illness: Study

“Still, the accuracy of both algorithms is surprisingly good, considering that the simpler model is based upon only three main variables and the more complex upon five main variables”, Pursiainen said.

In the future, the algorithms still have to be validated in national and international external datasets, the researchers concluded. (IANS)