yusuke1997/dblp-id-title huggingface dataset:
Guiding maps of solvents for lithium-sulfur batteries via a computational data-driven approach
Ranks underlie outcome of combining classifiers: Quantitative roles for diversity and accuracy
Meet the authors: Yuxuan Zhao, Enmeng Lu, and Yi Zeng
A multi-scale unified model of human mobility in urban agglomerations
Atomist or holist? A diagnosis and vision for more productive interdisciplinary AI ethics dialogue
A multimodal LLM-agent framework for personalized clinical decision-making in hepatocellular carcinoma
Relevance, redundancy, and complementarity trade-off (RRCT): A principled, generic, robust feature-selection tool
The path toward equal performance in medical machine learning
Characterizing COVID-19 and Influenza Illnesses in the Real World via Person-Generated Health Data
Integration of large language models and federated learning
AI-enabled image fraud in scientific publications
Road map for research on responsible artificial intelligence for development (AI4D) in African countries: The case study of agriculture
Chemical-induced gene expression ranking and its application to pancreatic cancer drug repurposing
Benchmarking the robustness of the correct identification of flexible 3D objects using common machine learning models
Inference and Prediction Diverge in Biomedicine
Quantifying emergent complexity
Benchmark suites instead of leaderboards for evaluating AI fairness
Exploring complex and heterogeneous correlations on hypergraph for the prediction of drug-target interactions
Data and its (dis)contents: A survey of dataset development and use in machine learning research
A generalized AI system for human embryo selection covering the entire IVF cycle via multi-modal contrastive learning
Propagating variational model uncertainty for bioacoustic call label smoothing
Cluster-based human-in-the-loop strategy for improving machine learning-based circulating tumor cell detection in liquid biopsy
Strain data augmentation enables machine learning of inorganic crystal geometry optimization
Perception of fairness in algorithmic decisions: Future developers' perspective
Cellular State Transformations Using Deep Learning for Precision Medicine Applications
Optimal decision-making in high-throughput virtual screening pipelines
Missing data as data
Integrative resource for network-based investigation of COVID-19 combinatorial drug repositioning and mechanism of action
Open-source software for data science
Network embedding unveils the hidden interactions in the mammalian virome
Balancing innovation and integrity in peer review
Reducing overconfident errors in molecular property classification using Posterior Network
DAISM-DNN XMBD : Highly accurate cell type proportion estimation with in silico data augmentation and deep neural networks
Thinking about Trust: People, Process, and Place
EasyGraph: A multifunctional, cross-platform, and effective library for interdisciplinary network analysis
From screening to subtyping in a single glance
Mainzelliste: Ten years of pseudonymization, record linkage, and informed consent management
COVID-19 Is a Data Science Issue
SELFIES and the future of molecular string representations
The effect of neural network architecture on virtual H&E staining: Systematic assessment of histological feasibility
Data shadows: When data become tangible, material, and fragile
BIOMERO: A scalable and extensible image analysis framework
Argonaut: A Web Platform for Collaborative Multi-omic Data Visualization and Exploration
Predictive coding is a consequence of energy efficiency in recurrent neural networks
Predicting energy and stability of known and hypothetical crystals using graph neural network
Quantum processor-inspired machine learning in the biomedical sciences
BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation
A systematic survey of natural language processing for the Greek language
Challenging deep learning models with image distortion based on the abutting grating illusion
A systematic review of multimodal brain age studies: Uncovering a divergence between model accuracy and utility
Fairness and accountability of AI in disaster risk management: Opportunities and challenges
Off the Staff: An Experiment in Visualizing Notes from Music Scores
Contrastive learning improves critical event prediction in COVID-19 patients
Universal machine learning framework for defect predictions in zinc blende semiconductors
Improving molecular representation learning with metric learning-enhanced optimal transport
Artificial Stupidity: Data We Need to Make Machines Our Equals
A boundary-guided transformer for measuring distance from rectal tumor to anal verge on magnetic resonance images
Paired evaluation of machine-learning models characterizes effects of confounders and outliers
Deep forecasting of translational impact in medical research
An adaptive federated learning framework for clinical risk prediction with electronic health records from multiple hospitals
Noise regularization removes correlation artifacts in single-cell RNA-seq data preprocessing
⁠Advancing ethical AI in healthcare through interpretability
Toward ubiquitous sensing: Researchers turn WiFi signals into human activity patterns
UFPS: A unified framework for partially annotated federated segmentation in heterogeneous data distribution
B-factor prediction in proteins using a sequence-based deep learning model
Enhancing molecular design efficiency: Uniting language models and generative networks with genetic algorithms
Population-wide analysis of hospital laboratory tests to assess seasonal variation and temporal reference interval modification
GREEN: A lightweight architecture using learnable wavelets and Riemannian geometry for biomarker exploration with EEG signals
Enhanced metagenomic deep learning for disease prediction and consistent signature recognition by restructured microbiome 2D representations
Preview of "Interpretable systems biomarkers predict response to immune-checkpoint inhibitors"
Modern views of machine learning for precision psychiatry
Labels in a haystack: Approaches beyond supervised learning in biomedical applications
Hopfield and Hinton's neural network revolution and the future of AI
How Do Data Bolster Pandemic Preparedness and Response? How Do We Improve Data and Systems to Be Better Prepared?
Machine learning for guiding high-temperature PEM fuel cells with greater power density
Parallel Factor Analysis Enables Quantification and Identification of Highly Convolved Data-Independent-Acquired Protein Spectra
Detecting Asymmetric Patterns and Localizing Cancers on Mammograms
Topological data analysis of thoracic radiographic images shows improved radiomics-based lung tumor histology prediction
Spatial coherence in DNA barcode networks
Audio self-supervised learning: A survey
PhosNetVis: A web-based tool for fast kinase-substrate enrichment analysis and interactive 2D/3D network visualizations of phosphoproteomics data
Interpretable systems biomarkers predict response to immune-checkpoint inhibitors
Overcoming the Data Gap for the Remote Diagnosis of Skin Cancer
A Random Matrix Theory Approach to Denoise Single-Cell Data
Stabilizing deep tomographic reconstruction: Part A. Hybrid framework and experimental results
African genomic data sharing and the struggle for equitable benefit
Representing the dynamics of high-dimensional data with non-redundant wavelets
AI for science and global citizens
A view of the sustainable computing landscape
Human-centric AI: An interview with Edith Luhanga
Chemical composition: Hearing insect defensive volatiles
Electric Dreams of Ukiyo: A Series of Japanese Artworks Created by an Artificial Intelligence
The reanimation of pseudoscience in machine learning and its ethical repercussions
Health advertising on Facebook: Privacy and policy considerations
Efficient model selection for predictive pattern mining model by safe pattern pruning
The COVID-19 Drug and Gene Set Library
Handle with Care: Lessons for Data Science from Black Female Scholars
Feminicide and counterdata production: Activist efforts to monitor and challenge gender-related violence
Shapley variable importance cloud for interpretable machine learning
AI systems must not confuse users about their sentience or moral status
Blockchain humanitarianism and crypto-colonialism
Concepts and applications of digital twins in healthcare and medicine
FAIR, open, and free does not mean no restrictions
Modeling in systems biology: Causal understanding before prediction?
Robust importance sampling for error estimation in the context of optimal Bayesian transfer learning
Quantifying extreme failure scenarios in transportation systems with graph learning
A Blueprint for Identifying Phenotypes and Drug Targets in Complex Disorders with Empirical Dynamics
Meet the authors: Daisuke Komura and Shumpei Ishikawa
The tree-based pipeline optimization tool: Tackling biomedical research problems with genetic programming and automated machine learning
Systems thinking and efficiency under emissions constraints: Addressing rebound effects in digital innovation and policy
Restaining-based annotation for cancer histology segmentation to overcome annotation-related limitations among pathologists
Interactive analysis of single-cell data using flexible workflows with SCTK2
A hybrid approach for identifying drug repurposing candidates and their mechanisms: An interview with Vanessa Lage-Rupprecht and two co-authors
MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance
Unveiling value patterns via deep reinforcement learning in heterogeneous data analytics
Designing optimal convolutional neural network architecture using differential evolution algorithm
Stable clinical risk prediction against distribution shift in electronic health records
CellContrast: Reconstructing spatial relationships in single-cell RNA sequencing data via deep contrastive learning
A comprehensive survey on smart contract construction and execution: paradigms, tools, and systems
Detecting clinically relevant topological structures in multiplexed spatial proteomics using TopKAT
Visualization of associative exploration of temporal concepts via frequent patterns
A New Era for Space Life Science: International Standards for Space Omics Processing
Cite what you read, read what you cite
Digital data donations: A quest for best practices
Prediction of Compound Bioactivities Using Heat-Diffusion Equation
Will drones revolutionize home delivery? Let's get real..
The receiver operating characteristic curve accurately assesses imbalanced datasets
"Digits: for Good"; How Patterns Can Help
Using Machine Learning to Identify Adverse Drug Effects Posing Increased Risk to Women
Why dignity is a troubling concept for AI ethics
A universal workflow for creation, validation, and generalization of detailed neuronal models
How could the United Nations Global Digital Compact prevent cultural imposition and hermeneutical injustice?
Nature-inspired self-organizing collision avoidance for drone swarm based on reward-modulated spiking neural network
Virtual Monoenergetic CT Imaging via Deep Learning
A method to computationally screen for tunable properties of crystalline alloys
Applications of knowledge graphs for food science and industry
Special collections for hot topics in data science: Call for proposals
Tackling the Challenges of 21 st -Century Open Science and Beyond: A Data Science Lab Approach
Different natural languages, equal importance
Using machine learning probabilities to identify effects of COVID-19
Three Strategies to Overcome Data-Sharing Challenges to Improve the Social Determinants of Health
Sex trouble: Sex/gender slippage, sex confusion, and sex obsession in machine learning using electronic health records
Multi-domain integrative Swin transformer network for sparse-view tomographic reconstruction
Bringing FAIRness to FDA data through visualization
Deep learning-enabled 3D multimodal fusion of cone-beam CT and intraoral mesh scans for clinically applicable tooth-bone reconstruction
Are we ready for a new paradigm shift? A survey on visual deep MLP
Social construction of XAI: Do we need one definition to rule them all?
Creation of a structured solar cell material dataset and performance prediction using large language models
DataDesc: A framework for creating and sharing technical metadata for research software interfaces
Predicting hydrogen storage in MOFs via machine learning
Brain-inspired bodily self-perception model for robot rubber hand illusion
Unified fair federated learning for digital healthcare
Continuous diagnosis and prognosis by controlling the update process of deep neural networks
Global and Local Tensor Factorization for Multi-criteria Recommender System
Disrupting adversarial transferability in deep neural networks
A case study of the Ancientbiotics collaboration
Honeycomb: An open-source distributed system for smart buildings
When accurate prediction models yield harmful self-fulfilling prophecies
Unraveling the complexity of rat object vision requires a full convolutional network and beyond
A transformer-based deep-learning approach for classifying brain metastases into primary organ sites using clinical whole-brain MRI images
Global understanding via local extraction for data clustering and visualization
The Veterans Affairs Precision Oncology Data Repository, a Clinical, Genomic, and Imaging Research Database
Understanding common human driving semantics for autonomous vehicles
Addressing bias in big data and AI for health care: A call for open science
Systematic indication extension for drugs using patient stratification insights generated by combinatorial analytics
Using Variational Multi-view Learning for Classification of Grocery Items
Data-centric approach to improve machine learning models for inorganic materials
Digital twins of the natural environment
AI-assisted facial analysis in healthcare: From disease detection to comprehensive management
Anthroponumbers.org: A quantitative database of human impacts on Planet Earth
Rapid Trust Calibration through Interpretable and Uncertainty-Aware AI
Classification of integers based on residue classes via modern deep learning algorithms
Hierarchical affinity landscape navigation through learning a shared pocket-ligand space
Enhancing phenotype recognition in clinical notes using large language models: PhenoBCBERT and PhenoGPT
One more thing ... Patterns 2.0
Describing Dataset Archetypes
A one-shot, lossless algorithm for cross-cohort learning in mixed-outcomes analysis
Recommendations for Services in a FAIR Data Ecosystem
Transcriptomic forecasting with neural ordinary differential equations
Intersectionality and reflexivity - decolonizing methodologies for the data science process
Avoid Oversimplifications in Machine Learning: Going beyond the Class-Prediction Accuracy
Data-driven artificial and spiking neural networks for inverse kinematics in neurorobotics
Upper limit of the transition temperature of superconducting materials
Systematic analysis of 50 years of Stanford University technology transfer and commercialization
Single-cell multi-modal GAN reveals spatial patterns in single-cell data from triple-negative breast cancer
cytoGPNet: Enhancing clinical outcome prediction accuracy using longitudinal cytometry data in small cohort studies
Gender bias, social bias, and representation in Bollywood and Hollywood
High Tech, High Risk: Tech Ethics Lessons for the COVID-19 Pandemic Response
When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey
Best holdout assessment is sufficient for cancer transcriptomic model selection
A comprehensive benchmark for COVID-19 predictive modeling using electronic health records in intensive care
Operational Readiness of Data: The Next Challenge for Data Professionals?
FaNDOM: Fast nested distance-based seeding of optical maps
Federated learning as a catalyst for digital healthcare innovations
A privacy-preserving approach for cloud-based protein fold recognition
Building less-flawed metrics: Understanding and creating better measurement and incentive systems
Prediction of allosteric sites and signaling: Insights from benchmarking datasets
Meet the authors: Hanchuan Peng, Peng Xie, and Feng Xiong
HeTDR: Drug repositioning based on heterogeneous networks and text mining
Can we share models if sharing data is not an option?
Are individuals who are positive about artificial intelligence also more unsure?
Fine-Pruning: A biologically inspired algorithm for personalization of machine learning models
On the sui generis value capture of new digital technologies: The case of AI
Focused learning by antibody language models using preferential masking of non-templated regions
dtoolAI: Reproducibility for Deep Learning
Type less, think more
Data analytics to evaluate the impact of infectious disease on economy: Case study of COVID-19 pandemic
Distributed information encoding and decoding using self-organized spatial patterns
Segmentation tracking and clustering system enables accurate multi-animal tracking of social behaviors
KG-COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response
The cost of unmodeled biological complexity in artificial neural networks
Capture the high-efficiency non-fullerene ternary organic solar cells formula by machine-learning-assisted energy-level alignment optimization
A machine learning framework to optimize optic nerve electrical stimulation for vision restoration
Using a deep generation network reveals neuroanatomical specificity in hemispheres
Few-shot deep learning for AFM force curve characterization of single-molecule interactions
The impact universe - a framework for prioritizing the public interest in the Internet of Things
Topic classification of electric vehicle consumer experiences with transformer-based deep learning
Knowledge transfer to enhance the performance of deep learning models for automated classification of B cell neoplasms
Data science through the lens of systems immunology
Rethinking data and metadata in the age of machine intelligence
Active sensing with predictive coding and uncertainty minimization
Open-source models for development of data and metadata standards
Computer-aided multi-objective optimization in small molecule discovery
Modularized neural network incorporating physical priors for future building energy modeling
Effect of imputation on gene network reconstruction from single-cell RNA-seq data
An AI-assisted tool for efficient prostate cancer diagnosis in low-grade and low-volume cases
Artificial image objects for classification of schizophrenia with GWAS-selected SNVs and convolutional neural network
Occupational models from 42 million unstructured job postings
Cryptocurrencies on the road to sustainability: Ethereum paving the way for Bitcoin
GAiN: An integrative tool utilizing generative adversarial neural networks for augmented gene expression analysis
How can big data shape the field of non-religion studies? And why does it matter?
The First Piece of the Pattern
Stabilizing deep tomographic reconstruction: Part B. Convergence analysis and adversarial attacks
A generic battery-cycling optimization framework with learned sampling and early stopping strategies
FAIM: Fairness-aware interpretable modeling for trustworthy machine learning in healthcare
A deep learning model for characterizing protein-RNA interactions from sequences at single-base resolution
The recent Physics and Chemistry Nobel Prizes, AI, and the convergence of knowledge fields
Assessing the adoption of the FAIR principles in Italian environmental research infrastructures
Preview of machine learning the quantum-chemical properties of metal-organic frameworks for accelerated materials discovery
A Searchable Database of Crystallization Cocktails in the PDB: Analyzing the Chemical Condition Space
Zero-shot personalization of speech foundation models for depressed mood monitoring
IoT-LLM: A framework for enhancing large language model reasoning from real-world sensor data
Neuron signal attenuation activation mechanism for deep learning
Machine learning accelerates identification of lithiated phases in X-ray images of battery hosts
Wheels of All Colors, Shapes, and Sizes Working Together: A Vision of Common Purpose in Data Science
Is AI overhyped?
Digital twins and the ethics of health decision-making concerning children
Connectome-based machine learning models are vulnerable to subtle data manipulations
Predicting drug toxicity at the intersection of informatics and biology: DTox builds a foundation
A quick battery charging curve prediction by artificial neural network
psHarmonize: Facilitating reproducible large-scale pre-statistical data harmonization and documentation in R
Data science enables X-ray vision
Human-centered explainability for life sciences, healthcare, and medical informatics
Exposing image splicing traces in scientific publications via uncertainty-guided refinement
AI in drug discovery: Applications, opportunities, and challenges
Low cost, uncertain value: Why cheap PV may still not become UK's main power source
Sensitive detection of synthetic response to cancer immunotherapy driven by gene paralog pairs
Predicting material microstructure evolution via data-driven machine learning
Extensions of the External Validation for Checking Learned Model Interpretability and Generalizability
Knowledge-driven learning, optimization, and experimental design under uncertainty for materials discovery
PYPE: A pipeline for phenome-wide association and Mendelian randomization in investigator-driven biobank scale analysis
No artificial intelligence authors, for now
Navigating an early career in genomics and data science, written from the perspective of a current PhD student
How deep can we decipher protein evolution with deep learning models
Levelized cost estimates of solar photovoltaic electricity in the United Kingdom until 2035
Correction: Paired evaluation of machine-learning models characterizes effects of confounders and outliers
Doing it right: Caring for and protecting patient information for US organ donors and transplant recipients
Bodily expressed emotion understanding through integrating Laban movement analysis
Evaluating progress in automatic chest X-ray radiology report generation
scTenifoldNet: A Machine Learning Workflow for Constructing and Comparing Transcriptome-wide Gene Regulatory Networks from Single-Cell Data
Efficient compression of SARS-CoV-2 genome data using Nucleotide Archival Format
The All of Us Research Program: Data quality, utility, and diversity
Dimensionality and dynamics for next-generation artificial neural networks
Anti-deficit is anti-racist and transformative
shinyDeepDR: A user-friendly R Shiny app for predicting anti-cancer drug response using deep learning
Principles of Effective Data Visualization
Statistics in everyone's backyard: An impact study via citation network analysis
Essential Regression: A generalizable framework for inferring causal latent factors from multi-omic datasets
An automated solution for measuring the progress toward FAIR research data
Situated language learning via interactive narratives
Pancreatlas: Applying an Adaptable Framework to Map the Human Pancreas in Health and Disease
FRAMM: Fair ranking with missing modalities for clinical trial site selection
Mortality prediction with adaptive feature importance recalibration for peritoneal dialysis patients
SenseFi: A library and benchmark on deep-learning-empowered WiFi human sensing
DeepDRiD: Diabetic Retinopathy - Grading and Image Quality Estimation Challenge
RDMkit: A research data management toolkit for life sciences
OpenML: Insights from 10 years and more than a thousand papers
Polymer informatics with multi-task learning
Scalable deeper graph neural networks for high-performance materials property prediction
Rapid personalized chemotherapy recommendation for cancer patients: An interview with Shaohua Ma and two members of his group
Breaking away from labels: The promise of self-supervised machine learning in intelligent health
Did chatbots miss their "Apollo Moment"? Potential, gaps, and lessons from using collaboration assistants during COVID-19
On the Importance of Data Transparency
Sequencing meets machine learning to fight emerging pathogens: A preview