Prostate Cancer

Entity-Aware Generation of Synthetic Clinical Progress Notes for Prostate Cancer using Large Language Model

Objectives: This study investigates large language models (LLMs) for clinical entity projection across substantial textual transformation. Specifically, we evaluate whether entities annotated in Spanish prostate cancer case reports can be preserved and explicitly projected when the source narratives are transformed into hospital-style clinical progress notes. Entity projection is treated as a gene...

Multiple versus pairwise sequence alignments for protein phylogenetics using foundation models

Phylogenetic inference is a common task in molecular and evolutionary biology and has conventionally required a multiple sequence alignment (MSA), a statistical model of amino acid substitutions, and an optimality principle. Recently, global models of amino acid substitutions have been inferred from millions of MSAs using transformer-based deep learning, resulting in protein foundation models (pFM...

Systematic toxicological study of PFOS/PFOA co-exposure driving prostate cancer: Core target identification, TME immune remodeling, and combination drug prediction

Background: Per- and polyfluoroalkyl substances (PFAS), particularly perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persisten...

HF-125, a first-in-class computer-modeled novel inhibitor of Tribbles 2, for therapy of enzalutamide resistant, neuroendocrine prostate cancer.

Second generation antiandrogens, such as enzalutamide, are commonly prescribed to treat advanced prostate cancer. However, enzalutamide resistant pros...

Screening for prostate cancer using PSA with and without MRI: systematic reviews with meta-analysis

Background: Previous recommendations on screening for prostate cancer relied on ongoing trials of screening with prostate-specific antigen (PSA), whic...

Development and Validation of a Multimodal AI-Based Model for Predicting Post-Prostatectomy Treatment Outcomes from Baseline Biparametric Prostate MRI

Prostate cancer (PCa) is the second most common cancer and cause of cancer death in American men. Existing risk prediction methods have limited accura...

Early treatment outcome prediction in metastatic castration-resistant prostate cancer utilizing 3-month tumor growth rate (g-rate) based machine learning model

Summary Background Once the treatment starts, early prediction of treatment benefit and its correlation with overall survival (OS) remains challenging...

Clinical Evaluation of a Digital Biomarker for Joint Swelling in Inflammatory Arthritis based on Automated Quantification of Dorsal Finger Fold Patterns

Objective: To clinically evaluate a digital biomarker, the Finger Fold Index (FFI), derived from the ratio of joint diameter to finger fold surface ar...

VALIDATION OF PROGRESS, A SIMPLE MACHINE-LEARNING DERIVED RISK STRATIFICATION SCORE FOR CASTRATION-RESISTANT PROSTATE CANCER

Purpose: Castration-resistant prostate cancer (CRPC) is characterized by marked clinical heterogeneity and poor long-term survival, underscoring the n...

Bridging the Applicator Gap with Data-Doping:Dual-Domain Learning for Precise Bladder Segmentation in CT-Guided Brachytherapy

Performance degradation due to covariate shift remains a major challenge for deep learning models in medical image segmentation. An open question is w...

Mechanistic Language Modeling and Oxygenated 3D Screening Reveal Berberine and Enzalutamide Synergy in Resistant Prostate Cancer

Resistance to androgen receptor inhibitors remains a primary challenge in prostate cancer treatment, yet identifying synergistic co-therapies is hinde...

STARS: Shared-specific Translation and Alignment for missing-modality Remote Sensing Semantic Segmentation

Multimodal remote sensing technology significantly enhances the understanding of surface semantics by integrating heterogeneous data such as optical i...

DeepPSA: A Geometric Deep Learning Model for PROTAC Synthetic Accessibility Prediction.

Proteolysis-targeting chimeras (PROTACs) have garnered significant attention in drug design due to their ability to induce the degradation of the targ...

Interactive Multi-Objective Probabilistic Preference Learning with Soft and Hard Bounds

High-stakes decision-making involves navigating multiple competing objectives with expensive evaluations. For instance, in brachytherapy, clinicians...

Automated Treatment Planning for Interstitial HDR Brachytherapy for Locally Advanced Cervical Cancer using Deep Reinforcement Learning

High-dose-rate (HDR) brachytherapy plays a critical role in the treatment of locally advanced cervical cancer but remains highly dependent on manual...

Automatic Treatment Planning using Reinforcement Learning for High-dose-rate Prostate Brachytherapy

Purpose: In high-dose-rate (HDR) prostate brachytherapy procedures, the pattern of needle placement solely relies on physician experience. We invest...

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning

Purpose: Accurate segmentation of clinical target volumes (CTV) and organs-at-risk is crucial for optimizing gynecologic brachytherapy (GYN-BT) trea...

Prostate Cancer Screening with Artificial Intelligence-Enhanced Micro-Ultrasound: A Comparative Study with Traditional Methods

Background and objective: Micro-ultrasound (micro-US) is a novel imaging modality with diagnostic accuracy comparable to MRI for detecting clinicall...

Photon-counting CT in cancer radiotherapy: technological advances and clinical benefits.

Photon-counting computed tomography (PCCT) marks a significant advancement over conventional Energy-integrating detector CT systems. This review highl...

A sub-meter resolution urban surface albedo dataset for 34 U.S. cities based on deep learning.

Surface albedo is a key determinant of urban heat islands, which modulates the amount of solar energy absorbed or reflected by urban surfaces, influen...