Diabetes has been steadily increasing over the past few decades worldwide and the majority of deaths are directly associated with diabetes each year. It's a chronic, metabolic disease classified by the high levels of blood glucose which drives major illness to the heart, blood vessels, eyes, kidneys, nerves, etc., Early diagnosis of diabetes and effective management and control of blood glucose, blood pressure and lipids, healthy diet, regular exercise, proper medications are effective approaches to reduce the complexity and risk of developing a neurocognitive disorder, heart disease and others for living well. As undiagnosed and untreated diabetes leads to worse health outcomes, regular screening is undoubtfully important to facilitate better treatment at the needed time. Fuzzy linear programming plays a key role in strategic planning, modeling, and analyzing the modern health care system for efficient control. Optimizing fuzzy linear programming-based technique is critical to determine the cause, appropriate diagnostic method, prevention, and solving a wide range of medical decision-making complications in neurocognitive disorders.

Neurocognitive disorder is a disease associated with brain function due to critical medical conditions. For instance, from recent studies, it's clear that diabetes intensifies the risks of dementia. Type 2 diabetes accelerated dementia due to various criteria like hypoglycemia, Alzheimer's disease, heart and blood pressure, etc. As diabetes raises the risk of damage to blood vessels in the brain it can lead to cognitive deficits. Thus, the diagnosis of diabetes needs to figure out all vital reasons relevant to neurocognitive disorders. The data from those criteria is changeable, impacting the progress of disease diagnosis. Fuzzy linear programming-based data mining with advanced techniques and technologies is essential in controlling a huge number of big data for predicting and diagnosing different categories of diabetic disease and precisely detecting the patients suffering from more than one disease including neurocognitive disorders which is quite a challenging task for medical specialists. Long-term health effects emerge if diabetes is not managed or perfectly treated. Fuzzy-based modern techniques are approached to identify the risk of diabetes for neurocognitive disorder among the patients, minimal errors, diminish mortality rate, less human intervention and effort, etc. Developing fuzzy linear programming-based medical diagnostic systems is required for high accuracy which is in high demand for treating diabetes-based neurocognitive complications.

This Special Issue outlines the significance of diagnosing diabetics and the neurocognitive problems with advances in fuzzy linear programming for high precision. Recently developed methods and technologies in medical data management are encouraged to provide better treatments. We welcome original research and review articles.

Potential topics include but are not limited to the following:

• Fuzzy linear programming-based multi-dimensional techniques for diabetes diagnosis and prevention of neurocognitive disorders
• Challenges and developments of fuzzy linear programming-based medical system applications in the diagnosis of neurocognitive impairments
• Fuzzy linear programming to enhance the interpretability of real-world medical data in decision-making neurocognitive operations
• Fuzzy linear programming for advanced detection and diagnosis of co-morbidity of diabetic patients with neurocognitive dysfunction
• Fuzzy linear programming optimization for computer-aided diabetic neuropathy detection and effects
• Intelligent fuzzy inference system and Internet of Things (IoT) for reducing uncertainty in the diagnosis of diabetics and dementia
• Fuzzy linear programming and new approaches in an assortment of type 2 diabetes and treatment for neurocognitive disorders
• Fuzzy mathematical analysis in diabetics and personalized medicine with precision for neurocognitive disorders
• Fuzzy logic algorithm-based automated insulin delivery (AID) for controlling diabetes and postoperative neurocognitive disorders
• Advances in fuzzy for diagnosis and monitoring of gestational diabetes mellitus (GDM) and neurocognitive impacts
• Fuzzy linear programming in early detection of cognitive decline in older and younger patients for brain health