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What is Artificial Intelligence, how is it revolutionising healthcare | UPSC Current Affairs News

(The Indian Express has launched a new series of articles for UPSC aspirants written by seasoned writers and erudite scholars on issues and concepts spanning History, Polity, International Relations, Art, Culture and Heritage, Environment, Geography, Science and Technology, and so on. Read and reflect with subject experts and boost your chance of cracking the much-coveted UPSC CSE. In the following article, Amit Kumar, a doctoral candidate at IIT Delhi, defines Artificial Intelligence and its healthcare benefits.)

Artificial Intelligence (AI) is the ability of machines, especially computers, to perform tasks that typically require human intelligence. These tasks include things like understanding language, recognising patterns, solving problems, and making decisions. 

Essentially, AI enables machines to think and learn from experience, just like humans do, but often at a much faster pace with access to vast amounts of data. 

Breakthroughs in computational power and big data accelerated AI’s capabilities in image and speech recognition, natural language processing, and autonomous systems. Today, AI continues to evolve, integrating into various industries, driving innovation, and transforming everyday life.

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Types and subsets 

AI can be classified into two types: Artificial Narrow Intelligence (ANI) also known as weak AI and Artificial General Intelligence (AGI) also referred to as strong AI. 

ANI is designed for specific tasks and excels within a narrow domain. Examples include virtual assistants like Siri, recommendation systems on platforms like Netflix, and image recognition software. ANI systems are highly specialised and cannot transfer their expertise to unrelated tasks. 


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In contrast, AGI aims to replicate human cognitive abilities, enabling it to perform any intellectual task a human can do. AGI would possess general reasoning skills, understand context, and adapt to new situations across various domains. It would be capable of autonomous learning and problem-solving without requiring task-specific programming.

Machine Learning (ML) and Deep Learning (DL) are subsets of AI but differ in complexity and capabilities. ML involves training algorithms to learn from data and make predictions and often requires manual feature extraction. 

DL, a subset of ML, uses neural networks with many layers (hence “deep”) to automatically learn features from large datasets. While ML works well with smaller datasets, DL requires vast amounts of data and computational power.

AI in Healthcare

AI is revolutionising healthcare for both non-communicable diseases (NCDs) and communicable diseases (CDs) by enhancing prevention, diagnosis, treatment, and management. 

In the realm of NCDs, AI algorithms excel at early detection and diagnosis by analysing medical images and patient data to identify conditions such as cancer, cardiovascular diseases, and diabetes often before symptoms appear. 

Personalised treatment plans are another major benefit, with AI systems tailoring drug dosages and therapies to individual patients, thereby optimising the management of chronic conditions like hypertension and asthma. 

Furthermore, AI-powered wearable devices and mobile apps enable continuous monitoring of health metrics in real-time, providing alerts and actionable insights that help manage chronic diseases more effectively and prevent complications. 

Predictive analytics is also a key application, as AI models can foresee disease progression and patient outcomes, allowing for proactive interventions and better resource allocation.

In the context of CDs, AI plays a critical role in outbreak prediction and surveillance by analysing diverse data sources such as social media and travel patterns to forecast and monitor disease outbreaks, facilitating timely public health responses. 

Benefits

Rapid diagnostics are significantly enhanced through AI, which can quickly and accurately identify pathogens in blood samples or through imaging, improving the speed and precision of infectious disease detection. 

AI also accelerates drug discovery by predicting effective compounds against specific pathogens, thus shortening development cycles for new antibiotics and antivirals. 

Additionally, AI supports telemedicine and remote monitoring, allowing healthcare providers to manage patients from a distance, which is especially crucial during pandemics and in regions with limited healthcare access.

Overall, AI’s integration into healthcare systems not only boosts efficiency and reduces costs but also significantly improves patient outcomes, contributing to a more robust and responsive global healthcare system.

AI-driven solutions 

Disease Diagnosis and Detection: AI algorithms can analyse medical images, such as X-rays, MRIs, and CT scans, with high accuracy, assisting in the early detection of diseases like cancer and tuberculosis.  For instance, AI systems have shown proficiency in identifying lung nodules, breast cancer, and diabetic retinopathy.

Drug Discovery and Development: AI revolutionises drug discovery and development by rapidly identifying potential drugs and predicting their effects. AI models analyse vast datasets to uncover patterns and relationships, accelerating target identification and lead optimisation. 

AI-driven simulations predict how drugs interact with biological systems, reducing the need for extensive laboratory experiments. In clinical trials, AI optimises trial design, patient selection, and data analysis, enhancing efficiency and success rates. 

By streamlining these processes, AI significantly reduces the time and cost of bringing new drugs to market, ultimately improving the availability of effective treatments for various diseases.

Predictive Analytics and Risk Assessment: AI models identify patterns and predict disease outbreaks, patient deterioration, and hospital readmissions. AI-driven tools assess individual patient risk, enabling early interventions and personalised care plans. 

By continuously monitoring health data from electronic health records (EHRs) and wearable devices, AI provides real-time insights and alerts healthcare providers to critical changes.

Precision medicine: AI revolutionises precision medicine by tailoring treatments to individual patients based on their unique genetic, environmental, and lifestyle factors. 

AI algorithms analyse vast datasets, including genomic sequences, medical histories, and real-time health data, to identify personalised treatment plans. It helps predict how patients will respond to specific therapies, optimising drug selection and dosages. 

This approach enhances the effectiveness of treatments, minimises adverse effects, and promotes preventive care.

Health Monitoring and Wearables: AI is transforming health wearables from trackers into proactive health partners. By analysing data from sensors, AI can detect patterns and predict health issues like heart problems or sleep apnea. This allows for early intervention and better chronic disease management. 

AI wearables can also monitor elderly individuals and remotely alert caregivers of falls or other emergencies.

Robotics and Automation: AI is the brainpower behind modern robotics. It equips robots with AI models to learn from experience and adapt to new situations. This enables robots to handle complex tasks, improve their precision over time, and make decisions based on sensor data. 

Imagine factory robots that can adjust their grip based on object shape or surgical robots performing delicate procedures. AI and robotics are revolutionising automation across industries.

Traditional Medicine: The Ayush Grid (Ministry of AYUSH) aims to improve the Ayush sector using AI to offer efficient, complete, affordable, and high-quality services to everyone through a secure and connected digital system.

Post Read Question

Define the concept of Artificial Intelligence (AI).

How is Artificial Narrow Intelligence (ANI) different from Artificial General Intelligence (AGI). Discuss with examples.

Discuss the ways Artificial Intelligence revolutionises healthcare in India.

Artificial Intelligence has the potential to democratise access to quality healthcare in India. Comment.

(Amit Kumar is a doctoral candidate at IIT Delhi. In the second part of the article, the author will discuss strides India has made in AI-driven healthcare solutions and challenges.) 

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