Drug, Healthcare and Patient Safety

Dove Medical Press is pleased to invite you to submit your research to an upcoming Article Collection on "Artificial Intelligence and Safety in Nephrology: Innovations and Impact in CKD, AKI, and Renal Disease", organized by Guest Advisors Dr. Rupesh Raina and Dr. Sidharth Kumar Sethi in Drug, Healthcare and Patient Safety. 

Artificial Intelligence (AI) has emerged as a significant tool in healthcare, transforming the landscape of disease diagnosis, management, and clinical monitoring. AI can dramatically increase the speed and efficiency of clinical practice, ranging from early diagnosis of AKI to improved treatment outcomes. Further applications of AI can aid in reducing rising healthcare costs and improving implementation of modern therapies. 

Acute Kidney Injury (AKI) affects 21.6% of adults and 33.7% of children globally, and chronic kidney disease (CKD) also demonstrates a significant incidence, impacting 10% of patients worldwide. AI can contribute to enhanced diagnosis and risk assessment and reduced treatment times, improving acute and chronic patient outcomes. Further advancements in AI technology able to access patient data can assist with predictive analytics and support nephrologists with longitudinal patient care. 

Subtopics include:

Diagnostic and screening interventions through to treatment, drug therapy, and surgery: safety issues in nephrology 

Identifying Patients at Risk of Kidney Disease: Utilising data from electronic health records(EHRs), AI algorithms could identify patients at risk of developing acute kidney injury (AKI) or chronic kidney disease (CKD) early. 

Artificial-intelligence imaging: Algorithms filter out noise in ultrasound, computed tomography (CT) and magnetic resonance imaging (MRI) scans, allowing them to diagnose nephrological conditions more accurately, which in turn can lead to earlier detection and reduced misdiagnosis by humans. 

Treatment

Individualised Treatment Plans: AI can utilise patient data, including genomics, to predict treatment outcomes and tailor treatment plans to individual circumstances, optimising the impact and reducing adverse effects. 

Complication Risks Predictive Analytics for Complication Risks: AI models could help to predict complications during treatments such as dialysis and help taking action in advance. Patient-Matched Clinical Trials Case-by-Case Patient-Matched Clinical Trials: AI can forge new ground by testing alternative drug formulations and dosages for individual patients. 

Drug Therapy

Applying Precision Medicine: AI can help to select the ideal cocktail of drugs for an individual patient with the lowest risk of side effects, based upon her genetic profile and medical history. 

Adjusting Dosages in Real-Time: AI systems can track patient responses to treatment and make recommendations for dosage adjustments, improving therapeutic effectiveness and safety. 

Surgery

Assistance in Invasive Procedures: Integrating AI in robotic systems can help surgeons achieve higher precision and lower risk of complications while performing nephrological surgeries through minimally invasive ways. 

Post-Operative Monitoring: AI can aid in early detection of post-operative complications, helping save lives by providing timely care.  

Acute Kidney Injury (AKI) 

AI-based Early Warning Signs of AKI: Create AI algorithms that can predict AKI using a deep learning model trained on EHR data, vital signs, laboratory results, and other indicators. 

Predictive Modeling for AKI Outcomes: Utilising AI to develop predictive models that can accurately predict adverse outcomes in AKI for risk stratification and guiding clinician decision-making towards optimal strategies. 

Chronic Kidney Disease (CKD)

AI for Predicting CKD Progression: Machine learning models are used to predict CKD progression, thereby optimising preventative actions and enhancing patient care. 

AI-Powered Remote Monitoring of CKD Patients: Building an AI-powered remote monitoring system to track CKD patients’ health, such that their condition can be constantly monitored and any deterioration detected early. 

Conclusion 

One area where AI will likely gain more traction in nephrology practice is the development of biomarkers that can be used for diagnostic, treatment, and surgical interventions. It has the potential to lead to better outcomes and more efficient healthcare delivery across the board, with a particular focus on AKI and CKD applications. 

All manuscripts submitted to this Article Collection will undergo desk assessment and peer review as part of our standard editorial process. Guest Advisors for this collection will not be involved in peer-reviewing manuscripts unless they are existing members of the Editorial Board. Please review the journal Aims and Scope and author submission instructions prior to submitting a manuscript. 

Keywords

• Artificial Intelligence
• CKD
• AKI
• LLM
• Dialysis

All manuscripts submitted to this Article Collection will undergo desk assessment and peer review as part of our standard editorial process. Guest Advisors for this collection will not be involved in peer-reviewing manuscripts unless they are existing members of the Editorial Board. Please review the journal Aims and Scope and author submission instructions prior to submitting a manuscript.

The deadline for submissions is 31 January 2025.

Please submit your manuscript on our website, quoting the promo code HKMMD to indicate that your submission is for consideration in this Article Collection.

Guest Advisors

Rupesh Raina, Akron Nephrology Associates/ Cleveland Clinic Akron General Medical Center, Akron, OH

[email protected]

Dr. Rupesh Raina completed medical school at King George's/CSM Medical College in Lucknow, India, and pursued residency in Internal Medicine and Pediatrics at MetroHealth Medical Center in Cleveland, OH. He completed fellowships in Nephrology & Hypertension at Cleveland Clinic and Pediatric Nephrology at Rainbow Babies & Children's Hospital. Board-certified in Pediatric Nephrology and Nephrology, Dr. Raina is an active member of several professional associations, including the American Association of Pediatrics, American Medical Association, and American Society of Nephrology. He is a Fellow of both the American College of Physicians and the American Academy of Pediatrics.

Sidharth Kumar Sethi, Pediatric Nephrology & Pediatric Kidney Transplantation, Kidney and Urology Institute
Medanta, The Medicity Hospital, Gurgaon, India

[email protected]

View all papers in this article collection