Publications by authors named "Ahluwalia Puneet"

Article Synopsis
  • This study evaluated the effectiveness of machine learning and neural network models in predicting biochemical recurrence (BCR) in men after undergoing robot-assisted radical prostatectomy (RARP).
  • 516 patients were analyzed, with 234 developing BCR during the median follow-up period of 24 months.
  • Results indicated that XGBoost and radial basis function neural network (RBFNN) models outperformed traditional methods, showing higher accuracy in predicting BCR.
View Article and Find Full Text PDF

Context: The superiority of off-clamp robot-assisted partial nephrectomy (RAPN) over the on-clamp technique has recently been questioned by randomized controlled trials comparing the two techniques.

Objective: To systematically review the recent literature and perform a quantitative synthesis of data on the comparison of off-clamp versus off-clamp hilar control during RAPN.

Evidence Acquisition: A systematic search was performed in the PubMed, Embase, Web of Science, and Scopus databases for studies comparing off-clamp versus on-clamp RAPN in terms of perioperative and functional outcomes.

View Article and Find Full Text PDF
Article Synopsis
  • Skin lesion classification is vital for early detection and management of serious skin conditions, but traditional transfer learning models are not performing optimally.
  • A novel method combining attention mechanisms with ensemble-based deep learning techniques has been developed, using seven pre-trained models to improve classification accuracy significantly.
  • The study reports a mean accuracy increase from 95.30% to 99.52% with ensemble approaches, demonstrating high reliability and effectiveness for classifying skin lesions.
View Article and Find Full Text PDF

To compare perioperative outcomes following robot-assisted partial nephrectomy (RAPN) in patients with morbid obesity (body mass index (BMI > 40 kg/m)) and non-obese patients. Using the Vattikuti Collective quality initiative (VCQI) database for RAPN, data for morbidly obese and non-obese patients was obtained. Propensity scores were calculated for two treatment groups (morbidly obese vs.

View Article and Find Full Text PDF

Background: Partial nephrectomy is the preferred treatment option for the management of small renal masses. On-clamp partial nephrectomy is associated with a risk of ischemia and a greater loss of postoperative renal function, while the off-clamp procedure decreases the duration of renal ischemia, leading to better renal function preservation. However, the efficacy of the off- versus on-clamp partial nephrectomy for renal function preservation remains debatable.

View Article and Find Full Text PDF

Introduction: The literature on studies reporting trifecta or pentafecta outcomes following robot-assisted partial nephrectomy (RAPN) in Indian patients is limited. The primary aim of this study was to report and evaluate the factors predicting trifecta and pentafecta outcomes following RAPN in Indian patients using the multicentric Vattikuti collective quality initiative (VCQI) database.

Methods: From the VCQI database for patients who underwent RAPN, data for Indian patients were extracted and analyzed for factors predicting the achievement of trifecta and pentafecta following RAPN.

View Article and Find Full Text PDF

Objective: The aim of the study is to evaluate the effect of deferred androgen deprivation therapy on biochemical recurrence (BCR) and other survival parameters in node-positive prostate cancer patients after robot-assisted radical prostatectomy with bilateral extended pelvic lymph node dissection (RARP + EPLND).

Materials And Methods: Of the 453 consecutive RARP procedures performed from 2011 to 2018, 100 patients with no prior use of androgen deprivation therapy were found to be lymph node (LN) positive and were observed, with initiation of salvage treatment at the time of BCR only. Patients were divided into 1 or 2 LNs (67)-and more than 2 LNs (33)-positive groups to assess survival outcomes.

View Article and Find Full Text PDF

Robotic assistance is being increasingly utilised for nephron-sparing surgery for complex renal masses. We evaluated the outcomes of robot-assisted partial nephrectomy (RAPN) for cT1a versus cT1b + renal masses by a comparative analysis of trifecta outcomes between these two groups of patients. We utilised our prospectively maintained database to identify patients undergoing RAPN for cT1a (group 1,  = 41) and cT1b + (group 2,  = 37) renal masses from April 2016 to March 2020.

View Article and Find Full Text PDF

Introduction: Outcomes of robot-assisted partial nephrectomy (RAPN) depend on tumor complexity, surgeon experience and patient profile among other variables. We aimed to study the perioperative outcomes of RAPN for patients with complex renal masses using the Vattikuti Collective Quality Initiative (VCQI) database that allowed evaluation of multinational data.

Methods: From the VCQI, we extracted data for all the patients who underwent RAPN with preoperative aspects and dimensions used for an anatomical (PADUA) score of ≥10.

View Article and Find Full Text PDF

: The price of medical treatment continues to rise due to (i) an increasing population; (ii) an aging human growth; (iii) disease prevalence; (iv) a rise in the frequency of patients that utilize health care services; and (v) increase in the price. Artificial Intelligence (AI) is already well-known for its superiority in various healthcare applications, including the segmentation of lesions in images, speech recognition, smartphone personal assistants, navigation, ride-sharing apps, and many more. Our study is based on two hypotheses: (i) AI offers more economic solutions compared to conventional methods; (ii) AI treatment offers stronger economics compared to AI diagnosis.

View Article and Find Full Text PDF

A diabetic foot infection (DFI) is among the most serious, incurable, and costly to treat conditions. The presence of a DFI renders machine learning (ML) systems extremely nonlinear, posing difficulties in CVD/stroke risk stratification. In addition, there is a limited number of well-explained ML paradigms due to comorbidity, sample size limits, and weak scientific and clinical validation methodologies.

View Article and Find Full Text PDF

Objective: To compare perioperative outcomes following robot-assisted partial nephrectomy (RAPN) in patients with age ≥ 70 years to age < 70 years.

Methods: Using Vattikuti Collective quality initiative (VCQI) database for RAPN we compared perioperative outcomes following RAPN between the two age groups. Primary outcome of the study was to compare trifecta outcomes between the two groups.

View Article and Find Full Text PDF

Background: Ability to predict the risk of intraoperative adverse events (IOAEs) for patients undergoing partial nephrectomy (PN) can be of great clinical significance.

Objective: To develop and internally validate a preoperative nomogram predicting IOAEs for robot-assisted PN (RAPN).

Design, Setting, And Participants: In this observational study, data for demographic, preoperative, and postoperative variables for patients who underwent RAPN were extracted from the Vattikuti Collective Quality Initiative (VCQI) database.

View Article and Find Full Text PDF

The SARS-CoV-2 virus has caused a pandemic, infecting nearly 80 million people worldwide, with mortality exceeding six million. The average survival span is just 14 days from the time the symptoms become aggressive. The present study delineates the deep-driven vascular damage in the pulmonary, renal, coronary, and carotid vessels due to SARS-CoV-2.

View Article and Find Full Text PDF

Introduction: Literature on the factors predicting functional and oncological outcomes following robot-assisted radical prostatectomy (RARP) is sparse for the Indian population. Hence, the primary objective of this study was to develop preoperative and postoperative nomograms predicting these outcomes in patients with prostate cancer undergoing RARP.

Methods: This retrospective analysis identified the predictors of quadrifecta outcomes, i.

View Article and Find Full Text PDF
Article Synopsis
  • Parkinson's disease (PD) is serious and costly to treat, and recent advancements in machine learning (ML) can predict cardiovascular and stroke risks in PD patients, but challenges arise due to COVID-19's impact on these models.
  • The study explores the hypothesis that COVID-19 exacerbates heart and brain damage in PD patients and proposes a deep learning (DL) model that factors in COVID-19 lung damage, alongside various medical data, for better risk stratification.
  • Validation of the DL model demonstrated its effectiveness in stratifying cardiovascular/stroke risk in PD patients during the pandemic, while also addressing potential biases in artificial intelligence applications for early detection of these risks.
View Article and Find Full Text PDF

Objective: To compare perioperative outcomes following retroperitoneal robot-assisted partial nephrectomy (RPRAPN) and transperitoneal robot-assisted partial nephrectomy (TPRAPN).

Methods: With this Vattikuti Collective Quality Initiative (VCQI) database, study propensity scores were calculated according to the surgical access (TPRAPN and RPRAPN) for the following independent variables, i.e.

View Article and Find Full Text PDF

Purpose: The role of erectile dysfunction (ED) has recently shown an association with the risk of stroke and coronary heart disease (CHD) via the atherosclerotic pathway. Cardiovascular disease (CVD)/stroke risk has been widely understood with the help of carotid artery disease (CTAD), a surrogate biomarker for CHD. The proposed study emphasizes artificial intelligence-based frameworks such as machine learning (ML) and deep learning (DL) that can accurately predict the severity of CVD/stroke risk using carotid wall arterial imaging in ED patients.

View Article and Find Full Text PDF
Article Synopsis
  • * Timely detection of CVD complications in DR patients is essential, and since traditional CAD risk assessments can be costly, low-cost imaging methods like carotid B-mode ultrasound can be utilized for better risk stratification.
  • * The use of artificial intelligence (AI) in analyzing large data sets helps identify risk factors for atherosclerosis in DR patients, thus aiding in CVD risk assessment and highlighting the interconnection between DR, CAD, and their implications during the COVID-19 pandemic.
View Article and Find Full Text PDF

Primary objective of this study was to determine diagnostic accuracy of minichromosome maintenance 5 (MCM5) protein in patients with bladder cancer (BC). In this review, we searched electronic databases to identify studies on the diagnostic accuracy of MCM5 in patients with BC. We pooled sensitivity and specificities using DerSimonian-Laird random-effect analysis and followed PRISMA guidelines while conducting this review (CRD42021255609).

View Article and Find Full Text PDF

: Atherosclerosis is the primary cause of the cardiovascular disease (CVD). Several risk factors lead to atherosclerosis, and altered nutrition is one among those. Nutrition has been ignored quite often in the process of CVD risk assessment.

View Article and Find Full Text PDF

Robot-assisted radical prostatectomy (RARP) is challenging in men with prior history of transurethral resection of the prostate (TURP). Few studies analyze this peculiar group of patients, and hence we sought to investigate the outcome of RARP in post-TURP men. We interrogated our prospectively maintained database containing 643 patients who underwent RARP from January 2012 to December 2020.

View Article and Find Full Text PDF