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The new AI tools are making better drugs and predicting diseases.

"An AI model developed by the Beckman Institute enables precise medical diagnoses with visual maps for explanation, enhancing doctor-patient communication and facilitating early disease detection." (ScitechDaily, X Marks the Spot: AI’s Treasure Maps Lead to Early Disease Detection)


The GlycoSHIELD AI-based software will revolutionize drug development. The software can simulate the morphology of sugar coats in proteins. That makes it easier to simulate how proteins. And cell's ion pumps interact. Another tool that makes AI more powerful in drug development is new observation tools like nano-acoustic systems. Those systems with very accurate X-rays and other systems can search how neurotransmitters act between neurons. 

The ability to control pain requires the ability to deny the neuro-transmitters travel between neurons. The systems of tomorrow may use some other method than chemical opioids to deny neurotransmitters reach the receiving cell. Those methods can be acoustic systems that destroy neurotransmitters before they transmit the pain signal. Or there could be some kind of fat, that can collect neurotransmitters from the axon hole. The problem is how to transport that fat to the right point and how to remove that fat when the injury is improved or fixed. 

"A NIH-funded study led by Worcester Polytechnic Institute (WPI) aims to utilize artificial intelligence to guide chronic pain patients toward mindfulness-based treatments rather than opioids. By analyzing patient data through machine learning, the research seeks to identify individuals who would benefit most from non-pharmacological interventions, potentially reducing opioid dependence and offering more personalized care. This innovative approach, focusing on chronic lower back pain across diverse populations, could revolutionize pain management and healthcare costs. Credit: Melissa E. Arndt" (ScitechDaily, Avoiding Opiates – A New AI Prescription for Pain)


And that information makes it possible to create new treatments that can be suitable for replacing opioids. The nano-acoustic systems can trap neurotransmitters in the sound waves. Or the acoustic system can destroy those transmitters before they can travel between axons. The other version could be medicine, which marks those neurotransmitters that transport pain signals to immune cells that they must destroy or transport those neurotransmitters away. 

In some models, engineered fat cells. Or cells can put that fat between neurons in the case of pain. Those genetically engineered fat cells can collect or close those neurotransmitters in the fat. And when pain is over the immune cells can collect that fat away. This version requires genetical engineering so that the fat cell can mark this plague for immune cells so that they can remove it. And it must also tie those neurotransmitters. 

This is one vision for systems that can replace opioids. The AI can also collect and analyze information from different sources. That system makes it possible to combine complex data from complex sources. 




"GlycoSHIELD transforms the way sugar chains on proteins are modeled, facilitating drug development with its fast, user-friendly, and energy-efficient algorithm, marking a significant stride in both green computing and medical research. Model of the sugar shield (green) on the GABAA receptor (grey) in a membrane (red) generated by GlycoSHIELD. Credit: Cyril Hanus, Inserm, University Paris-Cité" (ScitechDaily, GlycoSHIELD: New Software Revolutionizes Drug Development)



By the way... 


The AI can predict medical diseases by combining data from other patients. And that thing makes the AI an ultimate assistant to doctors. But the AI can also predict things like volcanic eruptions and earthquakes. The AI can use similar algorithms in that process as it is used for analyzing humans. The sensors analyze different things, but they analyze temperature, earth oscillation, water flow in rivers, and other things like electricity. So the researchers can modify healthcare programs for that purpose. 

And this makes the AI a very good tool for predicting natural diseases. The AI collects datasets about things that happened before the volcano eruption. Then this system compares this dataset with data that sensors give about volcanoes. This makes the AI predict the eruptions. 

But also things like houses with bad conditions have certain details that cause fire and other damages. The AI can collect data about the details of houses that have bad electric wires. Or some other problems. Then the AI can compare that information with other houses. 

The thing is that corrosion is always a similar process. The corrosive process with similar metal alloy is always the same in certain temperatures, radiation, and acidic environments. That means the AI can predict dangerous corrosion very accurately. And that helps the operators plan the service for those tubes and other systems. 

https://scitechdaily.com/avoiding-opiates-a-new-ai-prescription-for-pain/

https://scitechdaily.com/glycoshield-new-software-revolutionizes-drug-development/


https://scitechdaily.com/x-marks-the-spot-ais-treasure-maps-lead-to-early-disease-detection/


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