Generation of Synthetic Whole-Slide Image Tiles of Tumours from RNA-Sequencing Data via Cascaded Diffusion Models

Generation of Synthetic Whole-Slide Image Tiles of Tumours from RNA-Sequencing Data via Cascaded Diffusion Models

Information Science, Artificial Intelligence, Medicine, Basic Medical Sciences, Oncology,
cascaded diffusion models   RNA sequencing   synthetic images   tumors   machine learning   data scarcity   multimodal data  

Generation of Synthetic Whole-Slide Images of Tumors from RNA Sequencing Data via Cascaded Diffusion Models A recent study published in Nature Biomedical Engineering, titled “Generation of Synthetic Whole-Slide Image Tiles of Tumours from RNA-Sequencing Data via Cascaded Diffusion Models,” has garnered significant attention. This research, conducte...

Deep Geometric Learning with Monotonicity Constraints for Alzheimer’s Disease Progression

Information Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging,
Alzheimer's Disease   Geometric Modeling   Longitudinal Data   Missing Value Imputation   Neural Ordinary Differential Equations  

Using Monotonicity-Constrained Deep Geometric Learning to Predict Alzheimer’s Disease Progression Background Introduction Alzheimer’s Disease (AD) is a devastating neurodegenerative disorder that gradually leads to irreversible cognitive decline, eventually resulting in dementia. Early identification and progression prediction of this disease are c...

Modelling Dataset Bias in Machine-Learned Theories of Economic Decision-Making

Information Science, Artificial Intelligence, Humanities and Others,
dataset bias   economic decision-making   machine learning   neural networks   decision noise  

Background Introduction Over the long term, normative and descriptive models have been trying to explain and predict human decision-making behavior in the face of risk choices such as products or gambling. A recent study discovered a more accurate human decision model by training Neural Networks (NNs) on a new large-scale online dataset called choi...

Using Deep Neural Networks to Disentangle Visual and Semantic Information in Human Perception and Memory

Information Science, Artificial Intelligence, Medicine, Neurology, Life Sciences, Biophysics,
deep neural networks   visual information   semantic information   human perception   memory   visual-semantic representation   mental representation  

Differentiating Visual and Semantic Information in Human Perception and Memory Using Deep Neural Networks Introduction In cognitive science, the study of how humans recognize individuals and objects during perception and memory processes has long been of interest. Successful recognition of people and objects relies on matching representations gener...

Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning

Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning

Information Science, Artificial Intelligence, Medicine, Oncology, Life Sciences, Cell Biology,
Cancer   Deep Learning   Tumor origin   Cytology   Unknown primary  

Background Introduction Cancer of Unknown Primary (CUP) is a type of malignant disease that is confirmed to be metastatic through histopathology but whose primary site cannot be identified using conventional baseline diagnostic methods. CUP presents significant diagnostic and therapeutic challenges in clinical practice and is believed to account fo...

Medical History Predicts Phenome-Wide Disease Onset and Enables the Rapid Response to Emerging Health Threats

Information Science, Artificial Intelligence, Medicine, Environmental and Public Health,
medical history   disease prediction   rapid response   COVID-19   neural network   risk stratification  

Using Medical Records to Predict Common Disease Incidence and Support Rapid Response to Emerging Health Threats Research Background and Motivation The COVID-19 pandemic exposed systemic issues and a lack of data-driven guidance globally, significantly affecting the identification of high-risk populations and pandemic preparedness. Assessing individ...