Rohan Raju Dhanakshirur
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View article: A deep learning approach for objective evaluation of microscopic neuro-drilling craniotomy skills
A deep learning approach for objective evaluation of microscopic neuro-drilling craniotomy skills Open
This study introduces the first-ever well-annotated unbiased microscopic neuro-drilling effectiveness dataset and automated skill evaluation system, which surpasses the performance of an independent expert evaluator. It can be used as an u…
View article: Role of DECT-Based Imaging Biomarkers and Machine Learning to Predict Renal Cell Carcinoma Subtypes
Role of DECT-Based Imaging Biomarkers and Machine Learning to Predict Renal Cell Carcinoma Subtypes Open
The aim of the study was to assess and compare dual-energy CT (DECT) based quantitative parameters to differentiate between clear cell renal cell carcinoma (ccRCC) and non-ccRCC. This was a retrospective study including RCC patients who un…
View article: Utilizing large language models for gastroenterology research: a conceptual framework
Utilizing large language models for gastroenterology research: a conceptual framework Open
Large language models (LLMs) transform healthcare by assisting clinicians with decision-making, research, and patient management. In gastroenterology, LLMs have shown potential in clinical decision support, data extraction, and patient edu…
View article: Translating Ai Research into Practice: Clinical Validation and Real-World Deployment of an Ai-Based Micro-Suturing Skills Evaluation System
Translating Ai Research into Practice: Clinical Validation and Real-World Deployment of an Ai-Based Micro-Suturing Skills Evaluation System Open
View article: Predicting Renal Cell Carcinoma Subtypes and Fuhrman Grading Using Multiphasic CT-Based Texture Analysis and Machine Learning Techniques
Predicting Renal Cell Carcinoma Subtypes and Fuhrman Grading Using Multiphasic CT-Based Texture Analysis and Machine Learning Techniques Open
Objectives The aim of this study is to evaluate computed tomography texture analysis (CTTA) on multiphase CT scans for distinguishing clear cell renal cell carcinoma (ccRCC) from non-ccRCC and predicting Fuhrman's grade in ccRCC using open…
View article: Deep Learning for Detecting and Subtyping Renal Cell Carcinoma on Contrast-Enhanced CT Scans Using 2D Neural Network with Feature Consistency Techniques
Deep Learning for Detecting and Subtyping Renal Cell Carcinoma on Contrast-Enhanced CT Scans Using 2D Neural Network with Feature Consistency Techniques Open
Objective The aim of this study was to explore an innovative approach for developing deep learning (DL) algorithm for renal cell carcinoma (RCC) detection and subtyping on computed tomography (CT): clear cell RCC (ccRCC) versus non-ccRCC u…
View article: Correction: Deep learning for detection of iso-dense, obscure masses in mammographically dense breasts
Correction: Deep learning for detection of iso-dense, obscure masses in mammographically dense breasts Open
View article: Neurosurgery Simulation-based Skills Training: From Mannequins and Cadavers to Virtual Reality and Artificial Intelligence
Neurosurgery Simulation-based Skills Training: From Mannequins and Cadavers to Virtual Reality and Artificial Intelligence Open
Simulation in the neurosurgical context broadly refers to systems that either create or enhance the perceivable and sometimes interactable environment of the user. Adequate resident training requires hands-on experience, but operative neur…