As thousands suffocate and die from the COVID-19 virus, it is not a distant memory as people scramble to find intensive care beds and oxygen cylinders on Twitter, Facebook, and WhatsApp. The pandemic has also left many people unemployed, and the lockdown has forced them to migrate from cities to their villages in search of livelihood and work. This situation is not limited to India; The whole world is facing similar problems.
Although the world economy is slowly recovering, the loss of life is irreversible. When we look back on last year, it is clear that the world will not be able to handle another epidemic of this magnitude. With the advent of artificial intelligence (AI), we can better respond to disasters and even prevent them from happening in the first place. When an epidemic occurs, the government or relevant authorities try to control its spread and prevent its extinction.
Infection control requires rapid assessment, estimation of disease burden, and the allocation of medical personnel and facilities, including intensive care beds, oxygen, drugs, and medications. Large, rapid screening is necessary to identify infected individuals and isolate them from possible transmission of the disease. AI tools can play an important role in this analysis process.
For example, AI-based tools can analyze the sound of coughing to diagnose diseases such as tuberculosis or COVID-19 and help patients treat them. AI can also provide specialist physicians with diagnostic advice, for example, by detecting different features on chest X-rays that may indicate certain diseases, thereby shortening the turnaround time for diagnosis. The Central Tuberculosis Unit of India uses artificial intelligence for all aspects of TB care. One of these interventions is the automatic interpretation of the bacterial test line for the diagnosis of tuberculosis. Similar tools can be used for the sake of the sake of the sake of respect for the sake of communicable diseases. For the sake of Allah's sake, for the sake of Allah, the same apparatus can be made, and the same apparatus can be used in infectious diseases to speed up the diagnosis process.
Another important use of AI predictive models in epidemic control is to predict the spread of disease and help public health systems take action earlier. AI models can be used to predict future needs for patient infections, hospitalizations, intensive care beds, oxygen, and mortality in a given area. This model takes into account many factors such as population density, age distribution, and the effectiveness of different measures. Using these estimates, authorities can better allocate staff and medical supplies such as hospital beds, ventilators, and personal protective equipment to save lives. A large country like India needs a large number of contacts, as identifying and isolating cases is one of the most important aspects of disease control.
AI models can help streamline this process by analyzing data from mobile phones and other sources and identifying new trends quickly and efficiently. Resource allocation and distribution is always difficult in India where resources are limited. AI models can be used for supply chain optimization, reducing lead times, reducing costs, and predicting alternatives, enabling faster delivery. Government agencies around the world are using forecasting models to forecast the needs of healthcare facilities during the COVID-19 pandemic. AI forecasting models can also be used to inform policy decisions, manage relationships, and improve resource allocation.
For example, models can be trained to assess the effectiveness of neighborhood measures such as school and workplace closures and travel restrictions. By modeling various scenarios, policymakers can determine which interventions will be most effective in controlling the spread of the disease. AI models can accelerate the process of identifying treatments and developing treatments for emerging diseases by analyzing data from large numbers of clinical trials and medical records. The Indian government has been implementing artificial intelligence-driven media monitoring as part of the Disease Prevention Program (IDSP) since April 2022. The program established a media monitoring team and was reviewed at the National Center for Disease Control in Delhi in July 2008.
It is used to scan English and Hindi newspapers to identify those concerned and alert local authorities in a timely manner. Using artificial intelligence, the manual work of product analysis is automated and millions of articles are provided on the Internet. The AI tool scans national newspapers in 11 Indian languages, including English, to identify negative and relevant news.
The Integrated Health Information Platform (IHIP), created by the World Health Organization to support the IDSP document, states that from April 2022, the AI tool will system analyze an average of 80,000 health-related products per day. It is susceptible to seasonal changes, expansion, epidemics, etc., among others. found 20-200 adverse events depending on
means of the Media Monitoring Assistant (MSA) that manages this device. The MSA then selects the event from this list, confirming the location.
These summaries will be published and notified to local authorities once approved by the epidemiologist. As a result, while using AI to control infectious diseases presents some challenges, the potential benefits are enormous, saving lives and reducing economic and social impacts.
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