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2 Jordanian doctors honored for medical achievements abroad
Jordan News
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AMMAN — Two Jordanian doctors were honored abroad for
their medical achievements, local news outlets reported.اضافة اعلان
One scientist and expert in neurodevelopmental disorders was awarded in Qatar. Dr Noraldin Al-Deri, has developed a new device for diagnosing mental disorders, considered the first such device for children operating via intellectual technology and artificial intelligence, Khaberni reported.
The device is able to accurately assess a child’s mental acuity in 6.5 minutes and identify when children suffer from mental disorders such as autism spectrum disorder, attention deficit hyperactivity disorder, sensory disorders, speech delays, and motor development delays.
Qatar Foundation supported this invention from its initial stages to the final testing. The invention was recently chosen as one of the top seven out of 2,000 projects submitted to the Stars of Science Competition for the MENA region.
Currently, Deri represents Jordan in the 14th season of the competition.
The Director of Cheng Hsin General Hospital in Taipei, Taiwan, honored Jordanian scientist Dr Mohammad Bassam Khalifa Al-Manaseer, for developing an artificial intelligence algorithm capable of early detection of different types of cancer, such as liver and kidney cancer, and most recently breast cancer, according to Al-Ghad News.
Jordanian scientist, Dr. Mohammad Bassam Khalifa Al-Manaseer, is honored by the director of Cheng Hsin General Hospital in Taipei, Taiwan, for developing an artificial intelligence algorithm capable of early detection of different types of cancer, such as liver, kidney, and breast. (Photo: Twitter)
Manaseer published his last research paper on early detection of breast cancer using deep learning in the international medical journal, called “Cancers”.
Al-Ghad said Cancers is one of the important scientific publications in the study of oncology, with a high impact factor.
According to Manaseer, deep learning is one of the artificial intelligence branches that allows the machine to learn from data analysis by itself through cells and neural networks stimulation in the human brain.
He added that breast cancer’s early detection by reading X-ray images with the naked eye is the most common method, but the presence of different types of breast tissue makes the diagnosis process more complicated.
Deep learning, Manaseer explained, focuses on complex computational analysis for radiographs to recognize different patterns within the images, which usually requires thousands of images to train the algorithm and enhance its results.
Manaseer also pointed out that the experiments conducted on three databases of X-ray images proved that the new artificial intelligence algorithm is capable of reading X-ray images.
He said that the machine can detect breast cancer within a few seconds, with more than 96 percent accuracy rate. He noted that the new algorithm reduces the results of wrong tests, especially false negative results, with a rate of up to 4 percent.
Breast cancer is the most common type of cancer worldwide, with approximately one in 12 women developing breast cancer in their lifetime. It is also the first reason for cancer death among women.
Nearly 685,000 women died from breast cancer in 2020, according to a report by the World Health Organization.
Manaseer said he hoped that this algorithm will help doctors and radiologists in their work to get accurate early detection of breast cancer to speed up its treatment and reduce the financial and psychological consequences of it, and most importantly to reduce the cases of death resulting from it.
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Jordan News
One scientist and expert in neurodevelopmental disorders was awarded in Qatar. Dr Noraldin Al-Deri, has developed a new device for diagnosing mental disorders, considered the first such device for children operating via intellectual technology and artificial intelligence, Khaberni reported.
The device is able to accurately assess a child’s mental acuity in 6.5 minutes and identify when children suffer from mental disorders such as autism spectrum disorder, attention deficit hyperactivity disorder, sensory disorders, speech delays, and motor development delays.
Qatar Foundation supported this invention from its initial stages to the final testing. The invention was recently chosen as one of the top seven out of 2,000 projects submitted to the Stars of Science Competition for the MENA region.
Currently, Deri represents Jordan in the 14th season of the competition.
The Director of Cheng Hsin General Hospital in Taipei, Taiwan, honored Jordanian scientist Dr Mohammad Bassam Khalifa Al-Manaseer, for developing an artificial intelligence algorithm capable of early detection of different types of cancer, such as liver and kidney cancer, and most recently breast cancer, according to Al-Ghad News.
Jordanian scientist, Dr. Mohammad Bassam Khalifa Al-Manaseer, is honored by the director of Cheng Hsin General Hospital in Taipei, Taiwan, for developing an artificial intelligence algorithm capable of early detection of different types of cancer, such as liver, kidney, and breast. (Photo: Twitter)
Manaseer published his last research paper on early detection of breast cancer using deep learning in the international medical journal, called “Cancers”.
Al-Ghad said Cancers is one of the important scientific publications in the study of oncology, with a high impact factor.
According to Manaseer, deep learning is one of the artificial intelligence branches that allows the machine to learn from data analysis by itself through cells and neural networks stimulation in the human brain.
He added that breast cancer’s early detection by reading X-ray images with the naked eye is the most common method, but the presence of different types of breast tissue makes the diagnosis process more complicated.
Deep learning, Manaseer explained, focuses on complex computational analysis for radiographs to recognize different patterns within the images, which usually requires thousands of images to train the algorithm and enhance its results.
Manaseer also pointed out that the experiments conducted on three databases of X-ray images proved that the new artificial intelligence algorithm is capable of reading X-ray images.
He said that the machine can detect breast cancer within a few seconds, with more than 96 percent accuracy rate. He noted that the new algorithm reduces the results of wrong tests, especially false negative results, with a rate of up to 4 percent.
Breast cancer is the most common type of cancer worldwide, with approximately one in 12 women developing breast cancer in their lifetime. It is also the first reason for cancer death among women.
Nearly 685,000 women died from breast cancer in 2020, according to a report by the World Health Organization.
Manaseer said he hoped that this algorithm will help doctors and radiologists in their work to get accurate early detection of breast cancer to speed up its treatment and reduce the financial and psychological consequences of it, and most importantly to reduce the cases of death resulting from it.
Read more National news
Jordan News