Automated microscope & AI detect malaria parasites in clinical settings with 88% accuracy.
Highlights:
A group of international scientists has examined the precision of an automated microscope paired with artificial intelligence (AI) software in recognizing malaria parasites in blood samples from travelers within a real clinical environment. This method serves as an added approach for identifying the disease.
Every year, over 200 million people contract malaria, with more than 500,000 of these cases resulting in fatalities. The World Health Organization (WHO) advises diagnosing the disease caused by Plasmodium parasites through parasite-based methods prior to commencing treatment (1✔ ✔Trusted Source- Automated microscopes and AI software are used to identify malaria parasites in clinical settings
- The study tested system accuracy with an 88% match in diagnosing malaria from blood samples
- Automated malaria diagnosis through AI could reduce the workload for microbiologists and offer consistent results
Automated malaria detection system developed using AI and a microscope
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Quiz on Malaria
Malaria is a common parasitic disease of the tropics, resulting in a million deaths every year. It is most commonly found in tropical countries. The symptoms of malaria include fever with chills, headache, muscle aches, tiredness, nausea, vomiting, and diarrhea. Malaria fatalities can be reduced if they are detected early and treated appropriately
Malaria is a common parasitic disease of the tropics, resulting in a million deaths every year. It is most commonly found in tropical countries. The symptoms of malaria include fever with chills, headache, muscle aches, tiredness, nausea, vomiting, and diarrhea. Malaria fatalities can be reduced if they are detected early and treated appropriately
‘AI-powered automated microscope shows 88% accuracy in clinical testing. A step towards revolutionizing microscopic diagnosis. #AI #Microscope #Malaria’
In a recent study published in the Frontiers in Malaria journal, researchers analyzed over 1,200 blood samples obtained from travelers returning to the UK from countries where malaria is widespread. They evaluated the AI-microscope system's accuracy within a genuine clinical setting under optimal conditions. Study Achieves 88% Diagnostic Accuracy
Dr. Roxanne Rees-Channer, a researcher at The Hospital for Tropical Diseases at UCLH in the UK, mentioned, "The AI system identified malaria parasites at an accuracy rate of around 88%, compared to experts." She added that this performance level in a clinical context is a notable accomplishment for AI algorithms targeting malaria.Rees-Channer further emphasized, "This suggests that the system can indeed function as a valuable tool for malaria diagnosis in suitable situations." The team assessed samples using both manual light microscopy and the AI-microscope system. While 113 samples were manually identified as containing malaria parasites, the AI system correctly detected 99 samples as positive, achieving an accuracy rate of 88%.
AI-Enhanced Microscope Shows Promise in Malaria Detection
The potential advantages of automated malaria diagnosis were highlighted by the researchers. Rees-Channer noted that even experienced microscopists can make errors, particularly when dealing with high workloads. "The automated diagnosis of malaria using AI could alleviate this burden on microscopists and consequently increase the number of patients that can be managed," she explained. Additionally, these systems produce consistent outcomes and can be widely implemented, the researchers affirmed.Reference:
- Automated malaria detection system developed using AI and a microscope - (https://eandt.theiet.org/content/articles/2023/08/automated-malaria-detection-system-developed-using-ai-and-a-microscope/)
Source-Medindia
Artificial intelligence in Healthcare
Artificial intelligence (AI) in healthcare is the discipline using data intensive computer based solutions to improve patient care and outcome.
Artificial intelligence (AI) in healthcare is the discipline using data intensive computer based solutions to improve patient care and outcome.
Malaria
Malaria is caused by a parasite that enters blood through the bite of an infected mosquito. It is characterized by fever, vomiting, shivering, sweating and other symptoms.
Malaria is caused by a parasite that enters blood through the bite of an infected mosquito. It is characterized by fever, vomiting, shivering, sweating and other symptoms.
