23 papers · ranked by Valyu relevance
Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy + 4 more
'Thijs Vogels' 'Martin Jaggi' 'Tanja Käser' 'Mary-Anne Hartley'] | Vinitra Swamy | Malika Satayeva | Jibril Frej | Thierry Bossy | | --- | --- | --- | --- | | EPFL | EPFL | EPFL | EPFL | | vinitra.swamy@epfl.ch | malika.satayeva@epfl.ch | jibril.frej@epfl.ch | thierry.bossy@epfl.ch | | Thijs Vogels | Martin Jaggi |…
Thomas M. Deserno (né Lehmann), Heinz Handels, Klaus H. Maier-Hein (né Fritzsche), Sven Mersmann + 4 more
'Klaus H. Maier-Hein (né Fritzsche)' 'Sven Mersmann' 'Christoph Palm' 'Thomas Tolxdorff' 'Gudrun Wagenknecht' 'Thomas Wittenberg'] Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history…
Xin Tang, Jiawei Zhang, Yichun He, Xinhe Zhang + 9 more
Current biotechnologies can simultaneously measure multi-modality high-dimensional information from the same cell and tissue samples. To analyze the multi-modality data, common tasks such as joint data analysis and cross-modal prediction have been developed. However, current analytical methods are generally designed to…
Sachin Kumar, Sita Rani, Shivani Sharma, Hong Min + 1 more
Utilizing information from multiple sources is a preferred and more precise method for medical experts to confirm a diagnosis. Each source provides critical information about the disease that might otherwise be absent in other modalities. Combining information from various medical sources boosts confidence in the…
Shentong Mo, Paul Pu Liang
Biomedical data is inherently multimodal, consisting of electronic health records, medical imaging, digital pathology, genome sequencing, wearable sensors, and more. The application of artificial intelligence tools to these multifaceted sensing technologies has the potential to revolutionize the prognosis, diagnosis…
Md Abdur Rahaman, Yash Garg, Armin Iraji, Zening Fu + 6 more
Multi-modal learning has emerged as a powerful technique that leverages diverse data sources to enhance learning and decision-making processes. Adapting this approach to analyzing data collected from different biological domains is intuitive, especially for studying neuropsychiatric disorders. A complex…
Raffaele Marchesi, Nicolò Lazzaro, Walter Endrizzi, Gianluca Leonardi + 6 more
Integration of multimodal, multi-omics data is critical for advancing precision medicine, yet its application is frequently limited by incomplete datasets where one or more modalities are missing. To address this challenge, we developed a generative framework capable of synthesizing any missing modality from an…
Muhammad Zubair, Muzammil Hussai, Mousa Ahmad Al-Bashrawi, Malika Bendechache + 1 more
'Malika Bendechache' 'Muhammad Owais'] Abstract: Multi-modal medical image fusion (MMIF) is increasingly recognized as an essential technique for enhancing diagnostic precision and facilitating effective clinical decision-making within computer-aided diagnosis systems. MMIF combines data from X-ray, MRI, CT, PET…
Andrew A. Chen, Sarah M. Weinstein, Azeez Adebimpe, Ruben C. Gur + 5 more
To better understand complex human phenotypes, large-scale studies have increasingly collected multiple data modalities across domains such as imaging, mobile health, and physical activity. The properties of each data type often differ substantially and require either separate analyses or extensive processing to obtain…
FARHANA MANZOOR, VIBHUTI GUPTA, LUBNA PINKY, ZHANWEI WANG + 3 more
'ZHENBANG CHEN' 'YOUPING DENG' 'SUBASH NEUPANE'] Prostate cancer remains one of the most prevalent malignancies and a leading cause of cancer-related deaths among men worldwide. Despite advances in traditional diagnostic methods such as Prostate-specific antigen testing, digital rectal examination, and multiparametric…
Lingsen You, Jiaxin Yao, Yaoqing Qiu, Yu Wang + 4 more
Panvascular diseases (PVDs) stand as the leading cause of global mortality, necessitating a paradigm shift from local anatomical repair to the systemic restoration of vascular homeostasis. While intravascular optical imaging has revolutionized diagnosis, it remains a passive observation tool, restricted by “physical…
Yihao Li, Mostafa El Habib Daho, Pierre-Henri Conze, Rachid Zeghlache + 5 more
multimodal medical image classification Authors: ['Yihao Li' 'Mostafa El Habib Daho' 'Pierre-Henri Conze' 'Rachid Zeghlache' 'Hugo Le Boité' 'Ramin Tadayoni' 'Béatrice Cochener' 'Mathieu Lamard' 'Gwenolé Quellec'] Multimodal medical imaging plays a pivotal role in clinical diagnosis and research, as it combines…
Imran Ul Haq, Mustafa Mhamed, Mohammed Al-Harbi, Hamid Osman + 3 more
'Zuhal Y. Hamd' 'Zhe Liu' 'Fabiano Bini'] The majority of data collected and obtained from various sources over a patient’s lifetime can be assumed to comprise pertinent information for delivering the best possible treatment. Medical data, such as radiographic and histopathology images, electrocardiograms, and medical…
Hua-Jun Zhou, Fengtao Zhou, Zhao Chenyu, Yingxue Xu + 2 more
Future Directions Authors: ['Hua-Jun Zhou' 'Fengtao Zhou' 'Zhao Chenyu' 'Yingxue Xu' 'Luyang Luo' 'Hao Chen'] Abstract— The essence of precision oncology lies in its commitment to tailor targeted treatments and care measures to each patient based on the individual characteristics of the tumor. The inherent…
Authors not listed
Early prediction of drug-induced organ toxicity remains a major bottleneck in drug discovery and clinical pharmacotherapy. Most data-driven toxicity models behave as endpoint predictors: they output a label but provide limited transparency about why a compound is risky or which evidence channel dominated the decision.…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Marie Mueckstein, Kai Görgen, Stephan Heinzel, Urs Granacher + 2 more
The debate on the neural basis of multitasking costs evolves around neural overlap between concurrently performed tasks. Recent evidence suggests that training-related reductions in representational overlap in fronto-parietal brain regions predict multitasking improvements. Cognitive theories assume that overlap of…
D. M. Jensen, E. Zendehrouh, J. Liu, V. D. Calhoun + 1 more
Parallel independent component analysis (pICA) is a data-driven method that identifies the maximally independent components of multiple imaging modalities while simultaneously investigating the strength of their correlations. Researchers using pICA are given the option to use the suggested model order calculated by the…
Authors not listed
Battery research increasingly relies on advanced imaging, yet open access to such data remains rare, scattered across various sources, and difficult to find. The Battery Imaging Library (BIL) is the first open, curated collection of multi-modal and multi-length scale battery imaging datasets, accompanied by a…
Alexander Muacevic, John R Adler, Shubham Gupta, Pankaj Kaira + 4 more
Diagnostic radiology has progressed from basic X-ray imaging to a highly advanced, multimodality discipline that integrates high-resolution structural techniques, functional and molecular imaging, and computational analytics. This review synthesizes emerging trends in diagnostic radiology with a particular focus on…
Liping Zhang, Ben Zhong Tang, Zheng Zhao, Yu Xiong + 8 more
Targeted and controllable drug release at lesion sites with the aid of visual navigation in real-time is of great significance for precise theranostics of cancers. Benefiting from the marvellous features (e.g. bright emission and phototheranostic effect in aggregates) of aggregation-induced emission (AIE) materials…
David Buterez, Jon Paul Janet, Steven J. Kiddle, Pietro Liò
High-throughput screening (HTS), as one of the key techniques in drug discovery, is frequently used to identify promising drug candidates in a largely automated and cost-effective way. One of the necessary conditions for successful HTS campaigns is a large and diverse compound library, enabling hundreds of thousands of…
Amanda East, Michael Lee, Chang Jiang, Qasim Sikander + 1 more
The attachment of glucose to drugs and imaging agents enables cancer cell targeting via interactions with GLUT1 overexpressed on the cell surface. While an added benefit of this modification is the remarkable solubilizing effect of carbohydrates, in the context of imaging agents, aqueous solubility does not guarantee…