School Of Health Sciences

Permanent URI for this communityhttps://kr.cup.edu.in/handle/32116/102

Browse

Has files: NoSubject: search.filters.subject.Artificial intelligence

Search Results

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Opportunities and challenges in application of artificial intelligence in pharmacology
    (Springer Science and Business Media Deutschland GmbH, 2023-01-09T00:00:00) Kumar, Mandeep; Nguyen, T. P. Nhung; Kaur, Jasleen; Singh, Thakur Gurjeet; Soni, Divya; Singh, Randhir; Kumar, Puneet
    Artificial intelligence (AI) is a machine science that can mimic human behaviour like intelligent analysis of data. AI functions with specialized algorithms and integrates with deep and machine learning. Living in the digital world can generate a huge amount of medical data every day. Therefore, we need an automated and reliable evaluation tool that can make decisions more accurately and faster. Machine learning has the potential to learn, understand and analyse the data used in healthcare systems. In the last few years, AI is known to be employed in various fields in pharmaceutical science especially in pharmacological research. It helps in the analysis of preclinical (laboratory animals) and clinical (in human) trial data. AI also plays important role in various processes such as drug discovery/manufacturing, diagnosis of big data for disease identification, personalized treatment, clinical trial research, radiotherapy, surgical robotics, smart electronic health records, and epidemic outbreak prediction. Moreover, AI has been used in the evaluation of biomarkers and diseases. In this review, we explain various models and general processes of machine learning and their role in pharmacological science. Therefore, AI with deep learning and machine learning could be relevant in pharmacological research. � 2023, The Author(s) under exclusive licence to Maj Institute of Pharmacology Polish Academy of Sciences.
  • No Thumbnail Available
    Item
    Artificial Intelligence Bringing Newer Paradigms in the Diagnosis, Treatment, and Management of Psoriasis
    (Springer, 2023-10-04T00:00:00) Sharma, Ravi Kant; Sharma, Manu Rashmi; Mahendra, Aneet; Sharma, Ujjawal; Singh, Simranjit; Ramniwas, Seema; Sharma, Anil Kumar
    Purpose of Review: As we know, psoriasis is the most prevalent chronic inflammatory skin condition due to aberrant immune response which is characterized by clearly demarcated red or pink thick raised skin plaques sometimes covered with dry thin silvery white scales, formed due to the cytokine-driven hyperproliferation of epidermal keratinocytes. The abnormal functioning of immune-inflammatory pathways can cause various systemic conditions including cardiovascular diseases, chronic renal disease, and metabolic syndrome. Recent Findings: In comparison to other dermatological conditions, psoriasis has greater impact on the mental health of patients leading to increased risk of psychiatric comorbidities such as depression and anxiety.�The Articial intellingence could automate the analysis and provide contextual relevance, enhance clinical reliability,�assist the clinicians in communicating objectively, minimize human fatigue related errors, decrease mortality rates,�save medical expenditures and help in easy and early diagnosis of diseases including psoriasis. Summary: Therefore, development of better approaches for the diagnosis of psoriasis and determination of its classification type and severity are necessary for disease control and management and are the need of the hour. The artificial intelligence (AI) applications in medicine and healthcare are recently emerging due to advanced computing technologies and availability of abundant data on a variety of diseases including psoriasis. Hence, AI will certainly be a boon for the early detection and management of psoriasis patients necessitating further research in this area. � 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.