Cure For Epilepsy Not Far Away: New AI Tool Can Detect Brain Abnormalities That Cause Epileptic Seizures
This new toll can detect abnormalities in focal cortical dysplasia (FCDs), which are a leading cause of drug-resistant epilepsy.
This new toll can detect abnormalities in focal cortical dysplasia (FCDs), which are a leading cause of drug-resistant epilepsy.
Compared to other commonly available radiation machines, Radixact X9 Tomotherapy does not shoot the tumor at one go, but in a slice-by-slice manner.
Although memory loss is often one of the early signs of dementia, losing memory doesn't always mean you have dementia.
Researchers have identified four areas in the field of regenerative medicine where artificial intelligence (AI) would be of significant help. But the possibilities are endless.
The study revealed that the successful completion of this project carries significant potential for saving lives and improving patient healthcare provision.
Researchers have developed an AI algorithm that can successfully detect, segment, quantify and differentiate different types of brain injuries. Also, know the risk factors for brain injuries to prevent them for occurring.
Emerging technologies like artificial Intelligence (AI) and drones are playing a huge role in the fight against the deadly coronavirus. Read to know how these technologies are being implemented to contain the spread of this deadly virus.
According to the statement, the electrophysiological data collected during polysomnography -- the most comprehensive type of sleep study -- is well-positioned for enhanced analysis through AI and machine-assisted learning.
Technology has not only made our lives easier, but it's also saving lives by advancing the healthcare systems.
The researchers hope that the new AI tool will help them better understand how people with mental illnesses are doing and transform mental health care.
Artificial intelligence and robotics are gradually transforming the healthcare, simplifying the lives of patients, doctors and hospital administrators.
The new technique works with an 82 per cent reliability, and could replace the need for invasive finger-prick testing with a needle, especially for kids.
Researchers have revealed that Artificial Intelligence (AI) can help detect acute myeloid leukaemia (AML) - one of the most common forms of blood cancer - with high reliability.
According to a study published in the journal -- Cancer Immunology Research, using artificial Intelligence can predict if a lung-cancer patient would be benefitted from expensive immunotherapy or not. Read on to know more.
Researchers at the Institute of Cancer Research are applying the AI algorithm to many types of cancer to find out information for each about their sensitivity to treatment, likely paths of evolution and how to combat drug resistance.
A new study published in the journal 'Proceedings of the National Academy of Sciences' has unveiled a machine-learning algorithm that can spot abnormalities in pupil dilation that are predictive of autism spectrum disorder.
According to a study published in the journal JAMA Network Open, CXR-risk provides information that predicts long-term mortality, independent of radiologists' readings of the x-rays and other factors.
Scientists have recently developed a methodology that combines several Machine Learning (ML) algorithms to recognize depression more accurately using acoustic cues.
This new toll can detect abnormalities in focal cortical dysplasia (FCDs), which are a leading cause of drug-resistant epilepsy.
Compared to other commonly available radiation machines, Radixact X9 Tomotherapy does not shoot the tumor at one go, but in a slice-by-slice manner.
Although memory loss is often one of the early signs of dementia, losing memory doesn't always mean you have dementia.
Researchers have identified four areas in the field of regenerative medicine where artificial intelligence (AI) would be of significant help. But the possibilities are endless.
The study revealed that the successful completion of this project carries significant potential for saving lives and improving patient healthcare provision.
Researchers have developed an AI algorithm that can successfully detect, segment, quantify and differentiate different types of brain injuries. Also, know the risk factors for brain injuries to prevent them for occurring.
Emerging technologies like artificial Intelligence (AI) and drones are playing a huge role in the fight against the deadly coronavirus. Read to know how these technologies are being implemented to contain the spread of this deadly virus.
According to the statement, the electrophysiological data collected during polysomnography -- the most comprehensive type of sleep study -- is well-positioned for enhanced analysis through AI and machine-assisted learning.
Technology has not only made our lives easier, but it's also saving lives by advancing the healthcare systems.
The researchers hope that the new AI tool will help them better understand how people with mental illnesses are doing and transform mental health care.
Artificial intelligence and robotics are gradually transforming the healthcare, simplifying the lives of patients, doctors and hospital administrators.
The new technique works with an 82 per cent reliability, and could replace the need for invasive finger-prick testing with a needle, especially for kids.
Researchers have revealed that Artificial Intelligence (AI) can help detect acute myeloid leukaemia (AML) - one of the most common forms of blood cancer - with high reliability.
According to a study published in the journal -- Cancer Immunology Research, using artificial Intelligence can predict if a lung-cancer patient would be benefitted from expensive immunotherapy or not. Read on to know more.
Researchers at the Institute of Cancer Research are applying the AI algorithm to many types of cancer to find out information for each about their sensitivity to treatment, likely paths of evolution and how to combat drug resistance.
A new study published in the journal 'Proceedings of the National Academy of Sciences' has unveiled a machine-learning algorithm that can spot abnormalities in pupil dilation that are predictive of autism spectrum disorder.
According to a study published in the journal JAMA Network Open, CXR-risk provides information that predicts long-term mortality, independent of radiologists' readings of the x-rays and other factors.
Scientists have recently developed a methodology that combines several Machine Learning (ML) algorithms to recognize depression more accurately using acoustic cues.
