Traffic crashes present substantial challenges to human safety and socio-economic development in urban areas. Developing a reliable and responsible traffic crash prediction model is crucial to address growing public safety concerns and improve the sa...
The short-term risks associated with atmospheric trace gases, particularly carbon monoxide (CO), are critical for ecological security and human health. Traditional statistical methods, which still dominate the assessment of these risks, limit the pot...
Computer methods and programs in biomedicine
Sep 26, 2024
BACKGROUND AND OBJECTIVES: Post-traumatic stress disorder is a debilitating psychological condition that can manifest following exposure to traumatic events. It affects individuals from diverse backgrounds and is associated with various symptoms, inc...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Sep 24, 2024
BACKGROUND AND PURPOSE: During the ESTRO 2023 physics workshop on "AI for the fully automated radiotherapy treatment chain", the topic of deep learning (DL) segmentation was discussed. Despite its widespread use in radiotherapy, the time needed to ev...
INTRODUCTION: Artificial intelligence (AI) is exhibiting tremendous potential to reduce the massive costs and long timescales of drug discovery. There are however important challenges currently limiting the impact and scope of AI models.
Journal of imaging informatics in medicine
Sep 23, 2024
This study developed and validated a deep learning-based diagnostic model with uncertainty estimation to aid radiologists in the preoperative differentiation of pathological subtypes of renal cell carcinoma (RCC) based on computed tomography (CT) ima...
Journal of imaging informatics in medicine
Sep 23, 2024
Techniques are developed for generating uncertainty estimates for convolutional neural network (CNN)-based methods for registering the locations of lesions between the craniocaudal (CC) and mediolateral oblique (MLO) mammographic X-ray image views. M...
BACKGROUND: As we navigate towards integrating deep learning methods in the real clinic, a safety concern lies in whether and how the model can express its own uncertainty when making predictions. In this work, we present a novel application of an un...
. Previous methods for robustness evaluation rely on dose calculation for a number of uncertainty scenarios, which either fails to provide statistical meaning when the number is too small (e.g., ∼8) or becomes unfeasible in daily clinical practice wh...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Sep 17, 2024
BACKGROUND/PURPOSE: The use of artificial intelligence (AI) in radiotherapy (RT) is expanding rapidly. However, there exists a notable lack of clinician trust in AI models, underscoring the need for effective uncertainty quantification (UQ) methods. ...
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