MD MURAD HASAN@murad_1802018

Healthcare professionals often rely on radiology reports to diagnose diseases, but human errors and inefficiencies in traditional imaging processes can lead to misdiagnoses and delayed treatments (WHO, 2023). Medicus AI addresses these issues by employing deep learning algorithms to detect abnormalities in medical images with greater precision. (HIMSS, 2023). Environmental and Economic Impact of Traditional Medical Imaging: Medical imaging has long relied on plastic-based imaging films, CDs, and report covers, contributing significantly to environmental pollution. According to global estimates: • Plastic from imaging films: Approximately 1 billion imaging films used worldwide generate 20,000-30,000 metric tons of plastic waste annually. • Additional plastic waste: Covers, sleeves, and CDs contribute an estimated 5,000-10,000 metric tons annually. • Total plastic waste from medical imaging: 25,000-40,000 metric tons per year, costing the global healthcare sector $600 million to $1.3 billion annually (IMV Info, 2023). Medicus AI’s eliminates these waste materials, promoting sustainable healthcare solutions by integrating disease specific image detection AI models to analyze medical images and identify: • Fractures and infections • Lung diseases (e.g., pneumonia, tuberculosis, lung cancer) • Brain, spine, and joint abnormalities • Cardiology and obstetrics-related issues (e.g., heart diseases, fetal abnormalities) By providing automated, precise, and real-time diagnostic insights, Medicus AI enhances medical accuracy, reduces human errors, and supports healthcare professionals in making more informed decisions (OECD, 2023). The global medical imaging market, valued at $30 billion in 2023, is projected to grow 5-6% annually, driven by increasing demand for AI-driven solutions. With approximately 10 million doctors worldwide and thousands of diagnostic facilities, the adoption of AI in medical imaging is expected to reshape the future of healthcare (Market.us, 2023).

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