Prostate Cancer

Optimizing Dose-Response Decisions in Psoriatic Arthritis via Causal Machine Learning: A Real-World Evaluation of Secukinumab Treatment

Personalized treatment in psoriatic arthritis (PsA) remains challenging, particularly in guiding dose escalation decisions. We applied a causal machine learning framework to real-world data from the AQUILA study to evaluate the impact of secuki-numab dose escalation (150 mg to 300 mg) on disease activity and health-related quality of life (HR-QoL). Using double machine learning, we estimated both ...

Advancing patient care: Machine learning models for predicting grade 3+ toxicities in gynecologic cancer patients treated with HDR brachytherapy.

BACKGROUND: Gynecological cancers are among the most prevalent cancers in women worldwide. Brachytherapy, often used as a boost to external beam radiotherapy, is integral to treatment. Advances in computation, algorithms, and data availability have popularized the use of machine learning to predict patient outcomes. Recent studies have applied models such as logistic regression, support vector mac...

Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac using machine learning.

Meningococcal meningitis poses a significant public health burden in the meningitis belt region of sub-Saharan Africa. The introduction of the meningo...

Development and Validation of a Deep Learning Model Based on MRI and Clinical Characteristics to Predict Risk of Prostate Cancer Progression.

Purpose To validate a deep learning (DL) model for predicting the risk of prostate cancer (PCa) progression based on MRI and clinical parameters and c...

MoSH: Modeling Multi-Objective Tradeoffs with Soft and Hard Bounds

Countless science and engineering applications in multi-objective optimization (MOO) necessitate that decision-makers (DMs) select a Pareto-optimal ...

PEMF-VTO: Point-Enhanced Video Virtual Try-on via Mask-free Paradigm

Video Virtual Try-on aims to seamlessly transfer a reference garment onto a target person in a video while preserving both visual fidelity and tempo...

Automating proton PBS treatment planning for head and neck cancers using policy gradient-based deep reinforcement learning

Proton pencil beam scanning (PBS) treatment planning for head and neck (H&N) cancers is a time-consuming and experience-demanding task where a large...

Enhancing Choroidal Nevus Position Identification through CNN-Based Segmentation of Eye Fundus Images.

Diagnosing choroidal nevus in color fundus images is challenging for clinicians not regularly practicing it. Machine learning (ML) has proven effectiv...

Identification of Plausible Candidates in Prostate Cancer Using Integrated Machine Learning Approaches.

BACKGROUND: Currently, prostate-specific antigen (PSA) is commonly used as a prostate cancer (PCa) biomarker. PSA is linked to some factors that frequ...

Initial Experience of Robot-Assisted Simple Prostatectomy with Hugo Robot-Assisted Surgery System: Step-by-Step Description of Two Different Techniques.

There are only a few clinical data on nononcologic procedures performed with the new Hugo™ robot-assisted surgery (RAS) system. Robot-assisted simple...

Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer.

UNLABELLED: Survival rates of patients with metastatic castration-resistant prostate cancer (mCRPC) are low due to lack of response or acquired resist...

Segmentation of Clinical Target Volume From CT Images for Cervical Cancer Using Deep Learning.

Segmentation of clinical target volume (CTV) from CT images is critical for cervical cancer brachytherapy, but this task is time-consuming, laborious...

A smart, practical, deep learning-based clinical decision support tool for patients in the prostate-specific antigen gray zone: model development and validation.

OBJECTIVE: Despite efforts to improve screening and early detection of prostate cancer (PC), no available biomarker has shown acceptable performance i...

Artificial Intelligence and Deep Learning for Brachytherapy.

In recent years, Artificial intelligence (AI), specifically deep-learning (DL) based methods, have been employed extensively to solve various problems...

Prostate Cancer Risk Prediction and Online Calculation Based on Machine Learning Algorithm.

Objective To build a prostate cancer (PCa) risk prediction model based on common clinical indicators to provide a theoretical basis for the diagnosis ...

Deep Learning using Pre-Brachytherapy MRI to Automatically Predict Applicator Induced Complex Uterine Deformation.

This novel deep-learning (DL) algorithm addresses the challenging task of predicting uterine shape and location when deformed from its natural anatomy...

Artificial intelligence can overcome challenges in brachytherapy treatment planning.

Diagnostic yield and outcome of transrectal ultrasound-guided prostate biopsy in Sri Lanka.

The study was aimed to determine the diagnostic yield and outcome of transrectal ultrasound-guided prostate biopsy (TRUSPB) in a cohort of Sri Lankan ...

[Comparison of single incision robot-assisted laparoscopic radical prostatectomy with and without extraperitoneal special channel device].

To compare the clinical effects of single-incision robot-assisted laparoscopic radical prostatectomy (RARP) with and without extraperitoneal special ...

Artificial Intelligence-assisted Prostate Cancer Diagnosis: Radiologic-Pathologic Correlation.

The classic prostate cancer (PCa) diagnostic pathway that is based on prostate-specific antigen (PSA) levels and the findings of digital rectal examin...