Science & Technology MCQs - 2026-10-24

Key challenges for the widespread adoption of AI in healthcare include ensuring data privacy and security, addressing algorithmic bias that could lead to disparities in diagnosis, and navigating complex regulatory approval processes for AI-powered medical devices. While computing power is a factor, it's less of a bottleneck than these ethical and logistical concerns. AI is highly capable of processing medical data, and the cost of traditional tools is not a challenge for AI adoption.

AI models are demonstrating significant promise across various medical fields for early disease detection, especially through advanced image analysis. This includes oncology for detecting early signs of cancer in scans, cardiology for identifying cardiovascular risks from retinal images, and neurology for spotting subtle changes indicative of neurodegenerative diseases like Alzheimer's or Parkinson's in MRI scans.

The most significant advantage of AI in early disease detection is its ability to process vast amounts of data (medical images, genomic data, electronic health records) with high speed and accuracy, identifying subtle patterns or markers that might be missed by human observation, thereby enabling earlier diagnosis and intervention. It complements, rather than replaces, human professionals and diagnostic tools, and does not provide cures.

The Polar Satellite Launch Vehicle (PSLV) is ISRO's workhorse for launching Earth Observation Satellites into Sun-Synchronous Polar Orbits (SSPO). It has a proven track record for reliably deploying a variety of remote sensing satellites. GSLV Mk III (now LVM3) is primarily used for heavier communication satellites into Geostationary Transfer Orbit, and SSLV is for smaller satellites.

The TRISHNA (Thermal infraRed Imaging Satellite for High-resolution Natural resource Assessment) mission is a joint venture between ISRO and CNES (French Space Agency). It is designed to provide high-resolution thermal infrared data for monitoring Earth's surface temperature, crucial for water resource management, agricultural monitoring, urban heat island studies, and understanding the Earth's energy balance.

The NISAR (NASA-ISRO Synthetic Aperture Radar) mission is a joint project between NASA and ISRO. It is designed to use dual-frequency L-band and S-band SAR to observe and measure changes in Earth's land and ice surfaces, providing data on ecosystems, ice mass, vegetation biomass, sea level rise, and natural hazards. Its primary objective is not solely atmosphere and weather patterns, but rather land and ice surface dynamics.