Identify the most appropriate imputation method for handling missing values in clinical structured datasets: a systematic review

M Afkanpour, E Hosseinzadeh, H Tabesh - BMC Medical Research …, 2024 - Springer
Background and objectives Comprehending the research dataset is crucial for obtaining
reliable and valid outcomes. Health analysts must have a deep comprehension of the data …

Handling missing values and imbalanced classes in machine learning to predict consumer preference: Demonstrations and comparisons to prominent methods

Y Liu, B Li, S Yang, Z Li - Expert Systems with Applications, 2024 - Elsevier
Consumer preference prediction aims to predict consumers' future purchases based on their
historical behavior-level data. Using machine learning algorithms, the prediction results …

Metformin is associated with reduced COVID-19 severity in patients with prediabetes

LE Chan, E Casiraghi, B Laraway, B Coleman… - Diabetes research and …, 2022 - Elsevier
Aims Studies suggest that metformin is associated with reduced COVID-19 severity in
individuals with diabetes compared to other antihyperglycemics. We assessed if metformin …

[HTML][HTML] Extremely missing numerical data in Electronic Health Records for machine learning can be managed through simple imputation methods considering …

P Ferri, N Romero-Garcia, R Badenes… - Computer Methods and …, 2023 - Elsevier
Abstract Background and objective Reusing Electronic Health Records (EHRs) for Machine
Learning (ML) leads on many occasions to extremely incomplete and sparse tabular …

Spatial distribution of tumour immune infiltrate predicts outcomes of patients with high-risk soft tissue sarcomas after neoadjuvant chemotherapy

S Pasquali, V Vallacchi, L Lalli, P Collini, M Barisella… - …, 2024 - thelancet.com
Background Anthracycline-based neoadjuvant chemotherapy (NAC) may modify tumour
immune infiltrate. This study characterized immune infiltrate spatial distribution after NAC in …

[HTML][HTML] Predicting nutrition and environmental factors associated with female reproductive disorders using a knowledge graph and random forests

LE Chan, E Casiraghi, J Reese, QE Harmon… - International journal of …, 2024 - Elsevier
Abstract Objective Female reproductive disorders (FRDs) are common health conditions that
may present with significant symptoms. Diet and environment are potential areas for FRD …

Enhancing Fairness and Accuracy in Machine Learning Through Similarity Networks

S Maghool, E Casiraghi, P Ceravolo - International Conference on …, 2023 - Springer
Abstract Machine Learning is a powerful tool for uncovering relationships and patterns
within datasets. However, applying it to a large datasets can lead to biased outcomes and …

Association of post-COVID phenotypic manifestations with new-onset psychiatric disease

B Coleman, E Casiraghi, TJ Callahan, H Blau… - Translational …, 2024 - nature.com
Acute COVID-19 infection can be followed by diverse clinical manifestations referred to as
Post Acute Sequelae of SARS-CoV2 Infection (PASC). Studies have shown an increased …

Prospective associations of physical activity and sedentary time in adolescence with cardiometabolic risk in young adulthood

A Husøy, E Kolle… - … and science in …, 2024 - pubmed.ncbi.nlm.nih.gov
Purpose: The relationship between sedentary time, physical activity, and cardiometabolic
risk factors during the transition from adolescence to adulthood remain uncertain. We …

Thrombosis risk prediction in lymphoma patients: A m ulti‐institutional, retrospective model development and validation study

S Ma, J La, KN Swinnerton, D Guffey… - American journal of …, 2024 - Wiley Online Library
Venous thromboembolism (VTE) poses a significant risk to cancer patients receiving
systemic therapy. The generalizability of pan‐cancer models to lymphomas is limited …