However, patient data consists of diverse types of data. By exploiting such data, multimodal approaches promise to revolutionize our ability to provide personalized care. Attempts to combine two modalities in a
([Martinez-Maldonado et al., 2017], [Echeverria et al., 2018]) used sensor data (coming from patient manikins used for healthcare training) to capture students’ interaction traces and identify the key aspects (e.g., instructor–student dynamics and movements) of the learning process. ...
visual tokens and text tokens, and uses bidirectional blocks with intramodal and intermodal attention to learn holistic representations of radiographs, the unstructured chief complaint and clinical history, and structured clinical information such as laboratory test results and patient demographic information....
Technological advances have made it possible to study a patient from multiple angles with high-dimensional, high-throughput multiscale biomedical data. In oncology, massive amounts of data are being generated, ranging from molecular, histopathology, radi
Effective learning strategies include group discussions, listening to podcasts or recordings of meetings, Q&A sessions, and holding debates. Auditory learners may have to talk through their ideas before reaching a conclusion, so it’s important to be patient and allow them to process the new infor...
Machine Learning for Multimodal Electronic Health Records-Based Research: Challenges and Perspectives 2023, Communications in Computer and Information Science PM2F2N: Patient Multi-view Multi-modal Feature Fusion Networks for Clinical Outcome Prediction 2022, Findings of the Association for Computational Lin...
Benign paroxysmal positional vertigo (BPPV) is a prevalent form of vertigo that necessitates a skilled physician to diagnose by observing the nystagmus and vertigo resulting from specific changes in the patient’s position. In this study, we aim to explo
Only by assimilating all these kinds of modalities can we recapitulate a holistic kind of patient representation. So, from a machine learning point of view, precision health amounts to learning a function that inputs a multimodal patient journey and then outputs key medic...
Multimodal AI enables faster and more accurate diagnoses, personalized treatment plans, and better patient outcomes in thehealthcare and pharmaceutical industries. With the ability to analyze multiple data modalities, including image data, symptoms, background, and patient histories, multimodal AI can hel...
Patient characteristics are described in Supplementary Table S1, while therapeutic agents received are indicated in Supplementary Table S2. Most patients were male (N = 59, 56.19%) with an average age of 45.76 ± 13.23 years at the date of transplant. The transplant source was either...