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@article{191690,
        author = {Palak Kumari},
        title = {AI-Powered Healthcare Innovations for Early Diagnosis},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {12},
        number = {no},
        pages = {28-33},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191690},
        abstract = {Artificial Intelligence (AI) is rapidly transforming the healthcare sector, particularly in early disease detection and tailored treatment strategies. This paper reviews how advancements in AI, especially through Machine Learning (ML) and Deep Learning (DL), are enhancing medical diagnostics by increasing accuracy, speeding up clinical decisions, and minimizing the risk of human error. Timely diagnosis is essential to halt disease progression, reduce treatment expenses, and improve patient outcomes, making AI-driven systems a cornerstone for future healthcare advancements.
Also, algorithms such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) demonstrate strong capabilities in analyzing complex medical datasets, ranging from imaging (X-rays, CT scans, MRIs) to Electronic Health Records (EHRs). These tools help identify subtle patterns often missed by traditional approaches, thereby supporting the prompt detection of ailments like cancer, diabetes, and cardiovascular diseases. Through predictive analytics and improved image interpretation, AI technologies deliver more reliable, data-driven decision support for physicians. 
This review further addresses ongoing challenges, such as dataset diversity, data privacy, algorithmic bias, and the necessity for transparency in AI-based decision-making. Recommendations include expanding dataset breadth, advancing Explainable AI (XAI), reinforcing regulatory oversight, and fostering collaboration between medical professionals and AI developers. The findings indicate that with responsible integration, AI can revolutionize early diagnosis by enabling more predictive, preventive, and individualized healthcare worldwide.},
        keywords = {Artificial Intelligence, Data Privacy, Deep Learning, Early Diagnosis, Healthcare Innovation, Machine Learning},
        month = {},
        }