Zobrazeno 1 - 10
of 3 720
pro vyhledávání: '"Fadillah, A"'
Autor:
Dumont, Marc, Plagnes, Valérie, Lachassagne, Patrick, Guérin, Roger, Nugraha, Bayu, Mohamad, Febriwan, Oudin, Ludovic, Fadillah, Arif, Valdès, Danièle, Brocard, Gilles, Bonjour, Jean-Luc, Saadi, Mohamed, Esneu, Anne-Sophie, Muhammad, Aswar, Hendarmawan, Dörfliger, Nathalie
Publikováno v:
Comptes Rendus. Géoscience, Vol , Iss , Pp 1-23 (2023)
Andesitic volcanic hydrosystems in Indonesia are mostly hydrogeologically unknown despite their socio-economic importance. The development of robust and easy-to-implement methodologies to conceptualize and quantify the water cycle components becomes
Externí odkaz:
https://doaj.org/article/34bebe86eabf48a695c5983fc3e99ba2
Autor:
Ridzuan, Muhammad, Saeed, Numan, Maani, Fadillah Adamsyah, Nandakumar, Karthik, Yaqub, Mohammad
Survival analysis plays a crucial role in estimating the likelihood of future events for patients by modeling time-to-event data, particularly in healthcare settings where predictions about outcomes such as death and disease recurrence are essential.
Externí odkaz:
http://arxiv.org/abs/2409.19901
Brain tumor segmentation is a fundamental step in assessing a patient's cancer progression. However, manual segmentation demands significant expert time to identify tumors in 3D multimodal brain MRI scans accurately. This reliance on manual segmentat
Externí odkaz:
http://arxiv.org/abs/2405.02852
Autor:
Sanjeev, Santosh, Maani, Fadillah Adamsyah, Abzhanov, Arsen, Papineni, Vijay Ram, Almakky, Ibrahim, Papież, Bartłomiej W., Yaqub, Mohammad
With the emergence of vision language models in the medical imaging domain, numerous studies have focused on two dominant research activities: (1) report generation from Chest X-rays (CXR), and (2) synthetic scan generation from text or reports. Desp
Externí odkaz:
http://arxiv.org/abs/2403.13343
Autor:
Saeed, Numan, Ridzuan, Muhammad, Maani, Fadillah Adamsyah, Alasmawi, Hussain, Nandakumar, Karthik, Yaqub, Mohammad
Predicting the likelihood of survival is of paramount importance for individuals diagnosed with cancer as it provides invaluable information regarding prognosis at an early stage. This knowledge enables the formulation of effective treatment plans th
Externí odkaz:
http://arxiv.org/abs/2403.10603
Deep learning (DL) models have been advancing automatic medical image analysis on various modalities, including echocardiography, by offering a comprehensive end-to-end training pipeline. This approach enables DL models to regress ejection fraction (
Externí odkaz:
http://arxiv.org/abs/2403.10164
Medical data often exhibits distribution shifts, which cause test-time performance degradation for deep learning models trained using standard supervised learning pipelines. This challenge is addressed in the field of Domain Generalization (DG) with
Externí odkaz:
http://arxiv.org/abs/2403.09400
Autor:
Maani, Fadillah, Hashmi, Anees Ur Rehman, Aljuboory, Mariam, Saeed, Numan, Sobirov, Ikboljon, Yaqub, Mohammad
Automated segmentation proves to be a valuable tool in precisely detecting tumors within medical images. The accurate identification and segmentation of tumor types hold paramount importance in diagnosing, monitoring, and treating highly fatal brain
Externí odkaz:
http://arxiv.org/abs/2403.09262
Predicting the future trajectories of pedestrians on the road is an important task for autonomous driving. The pedestrian trajectory prediction is affected by scene paths, pedestrian's intentions and decision-making, which is a multi-modal problem. M
Externí odkaz:
http://arxiv.org/abs/2402.19002
Echocardiography has become an indispensable clinical imaging modality for general heart health assessment. From calculating biomarkers such as ejection fraction to the probability of a patient's heart failure, accurate segmentation of the heart stru
Externí odkaz:
http://arxiv.org/abs/2310.00454