Prediction of biochemical failure in localized carcinoma of prostate after radical prostatectomy by neuro-fuzzy

Goyal, Neeraj Kumar; Kumar, Abhay; Acharya, Rajiba L.; Dwivedi, US; Trivedi, Sameer; Singh, Priyanka; Singh, T. N.

doi:10.4103/0970-1591.30258

Cited by 3 publications

(2 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…All patients were operated with standard technique of radical retropubic prostatectomy described by Walsh. [ 2 ] Incision was midline, extraperitoneal extending from the pubis to the umbilicus. Bilateral pelvic lymph node dissection was performed.…”

Section: Methodsmentioning

confidence: 99%

“…Out of these, retropubic radical prostatectomy has been established as the primary curative procedure. [ 1 2 ] It is the most frequently performed procedure and is performed in 52% of patients, followed by external radiotherapy or brachytherapy used in approximately 20% of patients. [ 1 ] Even though it is the most commonly performed procedure, it is not without complications.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Surgical complications of radical retropubic prostatectomy: A single institutional experience of seven years

2007

Self Cite

View full text Add to dashboard Cite

Aim: To determine the surgical complications of open retropubic radical prostatectomy. Materials and Methods: Fifty-nine cases of localized prostate cancer underwent retropubic radical prostatectomy in our department in the last seven years. Standard technique of open retropubic radical prostatectomy as described by Walsh was used. During follow-up cancer control and quality of life indices (potency and urinary continence) were noted. Result: Postoperative recovery of all patients except one was excellent. This patient required cardio-respiratory support and nine units of blood transfusion. Forty-nine out of 52 patients were continent, two had stress incontinence and one was totally incontinent at one year. Bladder neck contracture was present in eight out of 52 patients at one year. Forty-five patients were impotent at one year with or without oral tablet sildenafil. Cancer control was present in 45 out of 52 cases. Seven cases had biochemical failure at one year. Conclusion: Though retropubic radical prostatectomy is the standard treatment for early prostate cancer it is not without complications. It has a steep learning curve. More number of cases and refinement in technique is required to achieve world-class results.

show abstract

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Surgical complications of radical retropubic prostatectomy: A single institutional experience of seven years

2007

Self Cite

View full text Add to dashboard Cite

show abstract

A systematic review of the applications of Expert Systems (ES) and machine learning (ML) in clinical urology

Salem

Soria

Lund

et al. 2021

BMC Med Inform Decis Mak

View full text Add to dashboard Cite

Background Testing a hypothesis for ‘factors-outcome effect’ is a common quest, but standard statistical regression analysis tools are rendered ineffective by data contaminated with too many noisy variables. Expert Systems (ES) can provide an alternative methodology in analysing data to identify variables with the highest correlation to the outcome. By applying their effective machine learning (ML) abilities, significant research time and costs can be saved. The study aims to systematically review the applications of ES in urological research and their methodological models for effective multi-variate analysis. Their domains, development and validity will be identified. Methods The PRISMA methodology was applied to formulate an effective method for data gathering and analysis. This study search included seven most relevant information sources: WEB OF SCIENCE, EMBASE, BIOSIS CITATION INDEX, SCOPUS, PUBMED, Google Scholar and MEDLINE. Eligible articles were included if they applied one of the known ML models for a clear urological research question involving multivariate analysis. Only articles with pertinent research methods in ES models were included. The analysed data included the system model, applications, input/output variables, target user, validation, and outcomes. Both ML models and the variable analysis were comparatively reported for each system. Results The search identified n = 1087 articles from all databases and n = 712 were eligible for examination against inclusion criteria. A total of 168 systems were finally included and systematically analysed demonstrating a recent increase in uptake of ES in academic urology in particular artificial neural networks with 31 systems. Most of the systems were applied in urological oncology (prostate cancer = 15, bladder cancer = 13) where diagnostic, prognostic and survival predictor markers were investigated. Due to the heterogeneity of models and their statistical tests, a meta-analysis was not feasible. Conclusion ES utility offers an effective ML potential and their applications in research have demonstrated a valid model for multi-variate analysis. The complexity of their development can challenge their uptake in urological clinics whilst the limitation of the statistical tools in this domain has created a gap for further research studies. Integration of computer scientists in academic units has promoted the use of ES in clinical urological research.

show abstract

Predicting Biochemical Recurrence of Prostate Cancer Post-Prostatectomy Using Artificial Intelligence: A Systematic Review

Liu,

Zhang,

Woon

et al. 2024

Cancers

View full text Add to dashboard Cite

Background/Objectives: Biochemical recurrence (BCR) after radical prostatectomy (RP) is a significant predictor of distal metastases and mortality in prostate cancer (PCa) patients. This systematic review aims to evaluate the accuracy of artificial intelligence (AI) in predicting BCR post-RP. Methods: Adhering to PRISMA guidelines, a comprehensive literature search was conducted across Medline, Embase, Web of Science, and IEEE Xplore. Studies were included if they utilised AI to predict BCR in patients post-RP. Studies involving patients who underwent radiotherapy or salvage RP were excluded. This systematic review was registered on PROSPERO (International prospective register of systematic reviews) under the ID CRD42023482392. Results: After screening 9764 articles, 24 met the inclusion criteria. The included studies involved 27,216 patients, of whom 7267 developed BCR. AI algorithms developed using radiological parameters demonstrated higher predictive accuracy (median AUROC of 0.90) compared to algorithms based solely on pathological variables (median AUROC of 0.74) or clinicopathological variables (median AUROC of 0.81). According to the Prediction Model Risk of Bias Assessment Tool (PROBAST), the overall risk of bias was unclear in three studies due to ambiguous inclusion criteria and the exclusion of many patients because of missing follow-up data. In seven studies, the developed AI outperformed or was at least equivocal to traditional methods of BCR prediction. Conclusions: AI shows promise in predicting BCR post-RP, particularly when radiological data were used in its development. However, the significant variability in AI performance and study methodologies highlights the need for larger, standardised prospective studies with external validation prior to clinical application.

show abstract

Prediction of biochemical failure in localized carcinoma of prostate after radical prostatectomy by neuro-fuzzy

Cited by 3 publications

References 10 publications

Surgical complications of radical retropubic prostatectomy: A single institutional experience of seven years

Surgical complications of radical retropubic prostatectomy: A single institutional experience of seven years

A systematic review of the applications of Expert Systems (ES) and machine learning (ML) in clinical urology

Predicting Biochemical Recurrence of Prostate Cancer Post-Prostatectomy Using Artificial Intelligence: A Systematic Review

Contact Info

Product

Resources

About