No abstract available.
Diagnosis* ; Polycystic Kidney Diseases*

No abstract available.
Diagnosis* ; Polycystic Kidney Diseases*

No abstract available.
Diagnosis* ; Female ; Humans ; Polycystic Kidney Diseases*

PURPOSE: To evaluate the characteristic CT findings of neuroblastoma, we studied neurobalstomas. METHODS AND MATERIALS: We analysed CT findings of available 25 cases among pathologically proved 51 neurobalstomas from Jan. 1983 to Sept. 1990. RESULTS: The most frequent site of origin is adrenl gland (40%) and the second is retroperitoneum (32%) and the third ismediastinum (16%). Characteristic CT findings are as follows:Calcifications within the tumor is detected in 86% of abdominal neuroblastomas and 50% of mediastinal origin. Hemorrhagic and necrotic changes within the tumor is noted at 86% in the tumor of abdominal origin and 25% in mediastinal neuroblastomas. Contrast enhanced study showed frequently septated enhanced appearance with/without solid contrast enhancement. Encasements of major great vessels such as aorta and IVC with/without displacement by metastatic lymphnodes or tumor are frequently seen in 90% of abdominal neuroblastomas. Multiple lymphadenopathy are detected in 95% of abdominal neurobalstomas and 25% of mediastinal neuroblastomas. The most common organ of contiguous direct invasion is kidney in 6 cases and the next one is liver but intraspinal canal invasion is also noted in 2 cases. CONCLUSION: We concluded that diagnosis of neuroblastoma would be easily obtained in masses of pediatric group from recognition of above characteristic findings.
Aorta ; Diagnosis ; Kidney ; Liver ; Lymphatic Diseases ; Neuroblastoma*

Child ; Humans ; Kidney Diseases ; diagnosis ; therapy ; Kidney Glomerulus

Kidney disease affects a large number of people around the world, imposing a significant burden to people's health and life. If early prediction, rapid diagnosis and prognosis prediction of kidney disease can be carried out, the health of patients will be better protected. Machine learning belongs to the category of artificial intelligence, which can be divided into supervised learning, unsupervised learning and reinforcement learning. With the increasing requirements for the processing and analyzing large-scale and high-dimensional data, machine learning is playing an increasingly important role in the medical domain, and the field of kidney disease is no exception. This article presents a comprehensive overview of the application progress of machine learning in kidney disease, aiming to make medical staff's decision-making in kidney disease more early, accurate and rapid, and better escort the life and health of patients.
Humans ; Artificial Intelligence ; Machine Learning ; Kidney ; Kidney Diseases/diagnosis*

BACKGROUND: Disease diagnosis is complicated since patients may demonstrate similar symptoms but physician may diagnose different diseases. There are a few number of investigations aimed to create a fuzzy expert system, as a computer aided system for disease diagnosis. METHODS: In this research, a cross-sectional descriptive study conducted in a kidney clinic in Tehran, Iran in 2012. Medical diagnosis fuzzy rules applied, and a set of symptoms related to the set of considered diseases defined. The input case to be diagnosed defined by assigning a fuzzy value to each symptom and then three physicians asked about each suspected diseases. Then comments of those three physicians summarized for each disease. The fuzzy inference applied to obtain a decision fuzzy set for each disease, and crisp decision values attained to determine the certainty of existence for each disease. RESULTS: Results indicated that, in the diagnosis of seven cases of kidney disease by examining 21 indicators using fuzzy expert system, kidney stone disease with 63% certainty was the most probable, renal tubular was at the lowest level with 15%, and other kidney diseases were at the other levels. The most remarkable finding of this study was that results of kidney disease diagnosis (e.g., kidney stone) via fuzzy expert system were fully compatible with those of kidney physicians. CONCLUSION: The proposed fuzzy expert system is a valid, reliable, and flexible instrument to diagnose several typical input cases. The developed system decreases the effort of initial physical checking and manual feeding of input symptoms.
Diagnosis ; Expert Systems ; Fuzzy Logic ; Humans ; Iran ; Kidney Calculi ; Kidney Diseases* ; Kidney*

Management of urologic patients is being gradually but dramatically altered with new advances in technical innovation and refinements of interventional uroradiology. The broadening of indications for percutaneous nephrostomy became possible only after it was learned that it is a safe and effective means of establishing access to the renal collecting system. Percutaneous stone extraction (Nephrolithotomy) and Endopyelotomy are now well established procedures. These techniques have clear advantages over the surgical treatment for the same conditions and will increase the quality of patient care and reduce health care cost.
Human ; Kidney Calculi/therapy ; Kidney Diseases/diagnosis ; Lithotripsy ; *Nephrostomy, Percutaneous/contraindications ; Urinary Tract Infections/diagnosis/therapy

OBJECTIVE: To explore the value of virtual touch tissue quantification (VTQ) in the diagnosis of renal allograft fibrosis and analyze its advantages and limitations. METHODS: The renal allografts of 54 patients with renal allograft biopsies or nephrectomy were assessed by Virtual Touch quantification of Siemens-Acuson S2000. RESULTS: Stiffness of renal allograft was significantly correlated to the value of VTQ (Spearman r=0.796, P<0.05). CONCLUSION VTQ is a new technique in the assessment of renal allograft fibrosis.
Diagnosis, Differential ; Elasticity Imaging Techniques ; Humans ; Kidney ; pathology ; Kidney Diseases ; diagnosis ; Kidney Transplantation ; Touch ; Transplantation, Homologous ; Transplants ; pathology

Child ; Diagnosis, Differential ; Humans ; Kidney Diseases ; diagnosis ; genetics ; therapy ; Nephrotic Syndrome ; diagnosis ; therapy ; Prenatal Diagnosis