By simplifying the task to a multi-label classification problem, our framework reduces the reliance on complex decoders, enabling a more efficient and accurate report generation process. This represents a significant shift from traditional methods that rely on intricate sequence generation models.
Aug 30, 2024
Aug 30, 2024 · In this paper, we propose a novel perspective: rethinking medical report generation as a multi-label classification problem.
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Sep 3, 2024 · Medical report generation is a multi-label classification problem that involves predicting multiple labels or diagnoses from medical images ...
4 days ago · Before training, multi-label classification is performed based on medical reports.
Nov 6, 2024 · The problem of predicting procedure codes from a given operative report can be successfully modelled as a multi-label classification task ...
In this paper, we propose a medical image report generation framework composed of four modules, including a Transformer encoder, a MIX-MLP multi-label ...
Medical Report Generation Is A Multi-label Classification Problem · Yijian Fan ... This paper proposes a novel perspective: rethinking medical report generation ...
Jul 23, 2024 · We aimed to develop and evaluate a multilabel classifier using natural language processing to identify factors contributing to medication-related incidents.
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Sep 9, 2024 · A set of multi‐label classifiers was evaluated on a public dataset of MI‐related complications to predict the outcomes of hospitalized patients with MI.
Multi-Label Classification · Medical Image Segmentation · Semantic Segmentation · Image Classification · Lesion Segmentation · Medical Diagnosis · Classification ...