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AI models predict lung cancer survival from PET/CT scans

By PulseAugur Editorial · [3 sources] ·

Researchers have developed new AI models, ATCS and MTS, to predict overall survival in lung cancer patients using PET/CT scans. These models outperformed a baseline TCS model, achieving AUCs of 0.794 and 0.793 respectively. ATCS showed better performance for shorter-term predictions (0.5-3 years), while MTS excelled at longer intervals (3.5-5 years). The study utilized data from 848 non-small cell lung cancer patients and found that combining different imaging features improved accuracy. AI

IMPACT These models offer improved risk stratification for lung cancer patients, potentially guiding personalized treatment and follow-up strategies.

RANK_REASON The cluster contains a research paper detailing new AI models for medical image analysis and survival prediction.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

AI models predict lung cancer survival from PET/CT scans

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The cluster contains a research paper detailing new AI models for medical image analysis and survival prediction.
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119 days old
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COVERAGE [3]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Time-Conditioned and Multi-Time Survival Prediction from 2D PET/CT Projections in Lung Cancer

    Accurate prediction of overall survival (OS) from positron emission tomography/computed tomography (PET/CT) can support personalized treatment and follow-up strategies in oncology. However, the impact of temporal modeling on imaging-based survival prediction remains insufficientl…

  2. arXiv cs.CV TIER_1 English(EN) · Ashish Chauhan, Sambit Tarai, Elin Lundstr\"om, Johan \"Ofverstedt, H{\aa}kan Ahlstr\"om, Joel Kullberg ·

    Time-Conditioned and Multi-Time Survival Prediction from 2D PET/CT Projections in Lung Cancer

    arXiv:2606.12140v1 Announce Type: new Abstract: Accurate prediction of overall survival (OS) from positron emission tomography/computed tomography (PET/CT) can support personalized treatment and follow-up strategies in oncology. However, the impact of temporal modeling on imaging…

  3. arXiv cs.CV TIER_1 English(EN) · Joel Kullberg ·

    Time-Conditioned and Multi-Time Survival Prediction from 2D PET/CT Projections in Lung Cancer

    Accurate prediction of overall survival (OS) from positron emission tomography/computed tomography (PET/CT) can support personalized treatment and follow-up strategies in oncology. However, the impact of temporal modeling on imaging-based survival prediction remains insufficientl…

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