Advances in healthcare technologies such as digital medical records, telemedicine, and artificial intelligence (AI) improve efficiency but raise cybersecurity concerns, making the protection of patient data more critical. This paper presents a secure framework that integrates steganography, cybersecurity, cryptography, and blockchain to protect the integrity and confidentiality of medical records and ensure digital trust of the transmission channel. The framework uses Stationary Wavelet Transform (SWT) and Least Significant Bit (LSB) steganography to embed compressed medical data in cover images, while RSA signatures ensure data integrity and AES encryption guarantees confidentiality. In addition, blockchain technology using smart contracts is used to immutably store the encrypted data and digital signatures, preventing tampering or unauthorized access. The system enables secure storage and retrieval of medical images and records. AI-based analysis was also performed to demonstrate that the system does not alter the intrinsic information present in the data. Clustering with k-mean and principal component analysis was used on the csv file to show that no alteration in the clustering structure. A deep convolutional network was used to predict classes of coloured images in the dataset before and after the system insertion extraction process. The results show minimal distortion in the stego images, with high PSNR and NCC values, and successful data recovery and verification through blockchain. This approach paves the way for secure medical data transmission and storage, digital sovereignty, with potential applications in telemedicine and other sensitive domains.