On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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9 results for “radiotherapy”

Precision Radiotherapy via Information Integration of Expert Human Knowledge and AI Recommendation to Optimize Clinical Decision Makingstat.ML

The paper integrates AI and expert knowledge to optimize radiotherapy decisions.

problem Optimizing radiation dose planning considering patient-specific information.

method Integrating Gaussian process models with deep neural networks to quantify uncertainty.

result Improves AI model performance and guides clinical decision making.

precision radiotherapy AI recommendation clinical decision making Gaussian process deep neural networks

2022-02-09abs ↗pdf ↗

Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapyphysics.med-ph

A ML-based method reconstructs 3D organ doses from 2D radiographs for pediatric abdominal radiotherapy.

problem Reconstructing detailed 3D dose distributions for childhood cancer survivors using limited 2D radiographs.

method Surrogate-free ML approach using 142 abdominal planning CTs, 300 artificial plans, and evolutionary algorithm.

result Accurate 3D dose reconstructions with MAEs ≤ 1.7 Gy for edge organs, validated on independent dataset.

ML radiotherapy organ dose pediatric abdominal

2020-02-17abs ↗pdf ↗

Exploiting Clinically Available Delineations for CNN-based Segmentation in Radiotherapy Treatment Planningcs.LG

CNNs can be trained with clinically available segmentations for OARs in radiotherapy.

problem Lack of dedicated training volumes for CNNs in radiotherapy.

method Used clinically available segmentations from PACS, applied multi-label segmentation, empirically assessed training set size.

result Clinically available segmentations can be used to train an accurate OAR segmentation model.

CNNs radiotherapy segmentation PACS multi-label

2019-11-12abs ↗pdf ↗

CAST: Time-Varying Treatment Effects with Application to Chemotherapy and Radiotherapy on Head and Neck Squamous Cell Carcinomacs.LG

CAST models time-varying treatment effects in cancer patients.

problem Estimating treatment effects at fixed time points limits understanding of dynamic changes over time.

method CAST combines parametric and non-parametric methods to model continuous time-varying treatment effects.

result CAST reveals how treatment effects rise, peak, and decline over the follow-up period.

Causal machine learning Survival analysis Time-varying treatment effects Head and Neck Squamous Cell Carcinoma Chemotherapy

2025-05-09abs ↗pdf ↗

Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapycs.CV

Over half a million individuals are diagnosed with head and neck cancer each year worldwide. Radiotherapy is an important curative treatment for this disease, but it requires manual time consuming delineation of radio-sensitive organs at risk (OARs). This planning process can delay treatment, while also introducing int…

2018-09-12abs ↗pdf ↗

Automatic Online Quality Control of Synthetic CTseess.IV

Automates quality control for synthetic CTs generated from MR images.

problem Prevent downstream errors in RT treatment planning from synthetic CTs.

method Ensemble of sCT generators and uncertainty measure based on their disagreement.

result Uncertainty measure can detect input images outside expected MR distribution and sCT images with potential errors.

synthetic CTs quality control deep learning radiotherapy MR-to-CT synthesis

2019-11-12abs ↗pdf ↗

Estimating heterogeneous survival treatment effect in observational data using machine learningstat.AP

Study improves machine learning for estimating survival treatment effects.

problem Estimating heterogeneous survival treatment effects in observational data.

method Flexible machine learning methods in the counterfactual framework, including AFT-BART-NP.

result AFT-BART-NP consistently yields best performance in terms of bias, precision, and frequentist coverage.

machine learning survival analysis heterogeneous treatment effects propensity score prostate cancer

2020-08-17abs ↗pdf ↗

Bias-Aware Conformal Prediction for Metric-Based Imaging Pipelinesstat.ML

Study improves confidence measures in medical imaging pipelines by addressing bias.

problem Bias in metric-based imaging pipelines compromises the efficiency of prediction intervals.

method Formalized symmetric and asymmetric CP formulations, analyzed bias effects, and validated empirically.

result Symmetric intervals are inflated by bias, while asymmetric intervals remain unaffected.

Bias Conformal Prediction Medical Imaging Confidence Intervals Radiation Therapy Planning

2024-10-07abs ↗pdf ↗

Whole-brain substitute CT generation using Markov random field mixture modelsstat.AP

Computed tomography (CT) equivalent information is needed for attenuation correction in PET imaging and for dose planning in radiotherapy. Prior work has shown that Gaussian mixture models can be used to generate a substitute CT (s-CT) image from a specific set of MRI modalities. This work introduces a more flexible cl…

2016-07-07abs ↗pdf ↗