Browsing by Author "Garg T."

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    Artificial intelligence in plant disease identification: Empowering agriculture
    (Academic Press Inc., 2024) Garg T.; Dwivedi P.; Mishra M.K.; Joshi N.C.; Shrivastava N.; Mishra V.
    The agricultural sector faces numerous challenges, such as infectious diseases, pest invasions, improper soil management, inadequate watering, and more. Among these, plant infectious diseases stand out as a leading cause of damage to crops. These diseases, impacting plants, result from various factors like genetics, soil composition, precipitation, moisture levels, humidity, temperature, and wind. In recent times, there has been a significant increase in the prevalence of plant infectious diseases. Pathogens like viruses, bacteria, and fungi consistently pose threats to plants, leading to substantial global crop yield losses during disease outbreaks. Unfortunately, disease identification and diagnosis typically occur at an advanced stage, causing significant agricultural setbacks. Given the impact of plant diseases on the nutritional value of fruits, vegetables, organic products, and cereals, timely identification is crucial during cultivation. Artificial intelligence (AI) has emerged as a pivotal tool in this context, leveraging its meticulous training capabilities for the effective identification of infectious plant diseases. This chapter illustrates how AI plays a vital role in identifying and diagnosing contagious plant diseases. � 2024 Elsevier Ltd
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    Current trends of computational tools and artificial intelligence in geriatric medicine
    (Elsevier, 2024) Awuah W.A.; Ou Yong B.M.; Mikhailova T.; Ng J.C.; Abdul-Rahman T.; Yarlagadda R.; Tedeschi A.J.; Miteu G.D.; Garg T.; David L.; Lansiaux E.; Huang H.; Nansubuga E.P.; Anand A.; Sikora K.; Isik A.; Debnath S.; Pramanik S.; Seth D.; Mukerjee N.; Narli F.; Sharma R.; Ghosh A.; Md Ashraf G.; Alexiou ?.
    As lifespans grow across the globe, so does the prevalence of neurodegenerative diseases among a rapidly expanding elderly demographic. Originating in the brain�the least understood organ in the human body�neurodegenerative diseases are caused by complex mechanisms that are challenging to study in a heterogeneous patient population. Machine learning, natural language processing, and other subfields of artificial intelligence have shown great promise as computational tools enabling physician-scientists to tackle these challenges on a potentially large scale. This chapter explores current applications of artificial intelligence in the classification, treatment, and management of the most common neurodegenerative diseases. � 2025 Elsevier Inc. All rights reserved.