Oncology/Hematology

Lung Cancer

Latest AI and machine learning research in lung cancer for healthcare professionals.

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The learning curve for single-port transaxillary robotic thyroidectomy (SP-TART): experience through initial 50 cases of lobectomy.

The new da Vinci® single-port (SP) robotic system, which utilizes a smaller incision and work space ...

Dec 2022 36536189
Iterative Reconstruction: State-of-the-Art and Future Perspectives.

Image reconstruction processing in computed tomography (CT) has evolved tremendously since its creat...

Dec 2022 36728734
Fast Near-Field Frequency-Diverse Computational Imaging Based on End-to-End Deep-Learning Network.

The ability to sculpt complex reference waves and probe diverse radiation field patterns have facili...

Dec 2022 36560139
Automation: A revolutionary vision of artificial intelligence in theranostics.

The last two decades have witnessed an extraordinary evolution of automation and artificial intellig...

Dec 2022 36509576
Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models.

Antibodies are an established class of human therapeutics. Epitope characterization is an important ...

Dec 2022 36641210
Deep-Learning Algorithm and Concomitant Biomarker Identification for NSCLC Prediction Using Multi-Omics Data Integration.

Early diagnosis of lung cancer to increase the survival rate, which is currently at a low range of m...

Dec 2022 36551266
Radiation therapist perceptions on how artificial intelligence may affect their role and practice.

INTRODUCTION: The use of artificial intelligence (AI) has increased in medical radiation science, wi...

Dec 2022 36479610
Feasibility of a lung airway navigation system using fiber-Bragg shape sensing and artificial intelligence for early diagnosis of lung cancer.

Currently early diagnosis of malignant lesions at the periphery of lung parenchyma requires guidance...

Dec 2022 36476838
A machine learning method for improving the accuracy of radiation biodosimetry by combining data from the dicentric chromosomes and micronucleus assays.

A large-scale malicious or accidental radiological event can expose vast numbers of people to ionizi...

Dec 2022 36473912
Effect of da Vinci robot-assisted versus traditional thoracoscopic bronchial sleeve lobectomy.

OBJECTIVE: To analyze the short-term effect of Da Vinci robot-assisted thoracoscopic (RATS) bronchia...

Nov 2022 36456441
X-ray dose profiles using artificial neural networks.

This paper introduces a novel computational method to simulate and predict radiation dose profiles i...

Nov 2022 36525911
Computed Tomography of the Spine : Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose.

The introduction of the first whole-body CT scanner in 1974 marked the beginning of cross-sectional ...

Nov 2022 36416936
Deep learning for predicting major pathological response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer: A multicentre study.

BACKGROUND: This study, based on multicentre cohorts, aims to utilize computed tomography (CT) image...

Nov 2022 36395737
Radiation Dosimetry, Artificial Intelligence and Digital Twins: Old Dog, New Tricks.

Developments in artificial intelligence, particularly convolutional neural networks and deep learnin...

Nov 2022 36379728
Deep reinforcement learning and its applications in medical imaging and radiation therapy: a survey.

Reinforcement learning takes sequential decision-making approaches by learning the policy through tr...

Nov 2022 36270582
Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation.

BACKGROUND: Online adaptive radiation therapy (RT) using hybrid magnetic resonance linear accelerato...

Nov 2022 36259384
Deep learning to estimate durable clinical benefit and prognosis from patients with non-small cell lung cancer treated with PD-1/PD-L1 blockade.

Different biomarkers based on genomics variants have been used to predict the response of patients t...

Nov 2022 36420269
Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology.

A model's ability to express its own predictive uncertainty is an essential attribute for maintainin...

Nov 2022 36323656
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