Developed CorrNN within IoMT to enhance CKD and CVD accuracy

Chronic Kidney Disease (CKD) &Cardiovascular Disease (CVD) would both be life-threatening parts of the process by renal impairment or reduced kidney functioning. Kidney cancer has been one of the worst cancers in the current study field, and while it was critical for the survival of clients' diagnostic and categorization. Early detection and treatment could prevent or delay the progression of this chronic illness to the point whereby hemodialysis or a kidney transplant have been the only options for preserving the person's life. Congestive Heart Failure (CHF) seems to be a chronic cardiac ailment that causes debilitating headaches & leads to higher mortality, disability, insurance premiums, and even a lower standard of living. The Electrocardiogram (ECG) seems to be a noninvasive & straightforward diagnostic tool that could reveal abnormalities in CHF. Manually ECG signal identification, on the other hand, was subject to mistakes due to the limited amplitude & length of ECG signals, which is neither accurate nor selective for CHF prognosis when used alone. The diagnosis accuracy & reproducibility of ECG signals in CHF may well be improved by using a technological and mechanical method.