Prostate Cancer

Fine-Tuning Open-Source Large Language Models to Improve Their Performance on Radiation Oncology Tasks: A Feasibility Study to Investigate Their Potential Clinical Applications in Radiation Oncology

Background: The radiation oncology clinical practice involves many steps relying on the dynamic interplay of abundant text data. Large language models have displayed remarkable capabilities in processing complex text information. But their direct applications in specific fields like radiation oncology remain underexplored. Purpose: This study aims to investigate whether fine-tuning LLMs with d...

Cancer-Net PCa-Seg: Benchmarking Deep Learning Models for Prostate Cancer Segmentation Using Synthetic Correlated Diffusion Imaging

Prostate cancer (PCa) is the most prevalent cancer among men in the United States, accounting for nearly 300,000 cases, 29% of all diagnoses and 35,000 total deaths in 2024. Traditional screening methods such as prostate-specific antigen (PSA) testing and magnetic resonance imaging (MRI) have been pivotal in diagnosis, but have faced limitations in specificity and generalizability. In this paper...

A memory-driven reinforcement learning model of phenotypic adaptation for anticipating therapeutic resistance in prostate cancer

While contemporary cancer treatment strategies have significantly prolonged the lives of patients, therapeutic resistance remains a predominant cause ...

Radiomics-Based Early Triage of Prostate Cancer: A Multicenter Study from the CHAIMELEON Project

Prostate cancer (PCa) is the most commonly diagnosed malignancy in men worldwide. Accurate triage of patients based on tumor aggressiveness and stagin...

A multi-modal deep learning framework for predicting PSA progression-free survival in metastatic prostate cancer using PSMA PET/CT imaging

PSMA PET/CT imaging has been increasingly utilized in the management of patients with metastatic prostate cancer (mPCa). Imaging biomarkers derived fr...

Artificial Intelligence quantified prostate specific membrane antigen imaging in metastatic castrate-resistant prostate cancer patients treated with Lutetium-177-PSMA-617

The VISION study1 found that Lutetium-177 (177Lu)–PSMA-617 (“Lu-177”) improved overall survival in metastatic castrate resistant prostate cancer (mCRP...

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 machin...

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 radio...

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...