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open source kaggle dataset 1 eye diseases classification dataset (Kaggle Inc)

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Kaggle Inc open source kaggle dataset 1 eye diseases classification dataset
Open Source Kaggle Dataset 1 Eye Diseases Classification Dataset, supplied by Kaggle Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/open+source+datasets/accuracy+dataset+forecasting+m5/pm41192815-128-4-5
Average 86 stars, based on 1 article reviews

open source kaggle dataset 1 eye diseases classification dataset - by Bioz Stars, 2026-11

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Article Title: Energy consumption forecasting in logistics considering environmental and operational constraints using FT-transformer architecture
Article Snippet: The dataset is freely available at online repository Kaggle URL: Dataset 1 (https:/www.kaggle.com/datasets/programmer3/energy-aware-logistics-scheduling-dataset)Dataset 2 (https:/www.kaggle.com/datasets/ziya07/ev-energy-consumption-dataset).

Article Title: Energy consumption forecasting in logistics considering environmental and operational constraints using FT-transformer architecture.
Article Snippet: The dataset is freely available at online repository Kaggle URL: Dataset 1 https://www.kaggle.com/datasets/programmer3/energy-aware-logisticsscheduling-dataset Dataset 2 https://www.kaggle.com/datasets/ziya07/ev-energy-consumption-dataset Authors Contributions The author Lai Yan fully contributed to this study.

Article Title: A hybrid ensemble deep learning framework with novel metaheuristic optimization for scalable malicious website detection.
Article Snippet: Limitations and Future Work While the proposed hybrid ensemble–deep learning framework demonstrates strong performance on the Kaggle URL dataset, several limitations remain that should be addressed in future studies.

Article Title: Deep learning-based phishing classification framework for accurate detection using optimized URL intelligence
Article Snippet: Dataset , Benchmark phishing URL dataset (PhiUSIIL, Kaggle, Mendeley).

Article Title: A hybrid ensemble deep learning framework with novel metaheuristic optimization for scalable malicious website detection
Article Snippet: While the proposed hybrid ensemble–deep learning framework demonstrates strong performance on the Kaggle URL dataset, several limitations remain that should be addressed in future studies.

Article Title: A dataset of exogenous variables and historical electricity demand for short-term load forecasting of the national interconnected electric system (SENI) in the Dominican Republic from 2021 to 2024
Article Snippet: Data accessibility , Repository: Kaggle - Short-Term Forecasting Dataset SENI Dominican Rep URL: https://www.kaggle.com/datasets/rafaeluceta/short-term-forecasting-dataset-seni-dominican-rep License: CC BY-NC-SA 4.0 , .

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$a ) and b ) Gene expression changes within infarcted left ventricle (‘infarct’) are marked at 24- and 48-hours post-MI, as assessed by hierarchical clustering and principal component analyses of the open-source GEO dataset GSE4648 . Analyses carried out using Geo2R and the open-source BART bioinformatics tool. c ) Differential gene expression patterns identified in 24-hour post-MI ventricle compared with sham control. cIAP2 (Birc3) is significantly upregulated. d ) LV infarct region gene expression timecourse of cIAP2 (maroon) and related transcripts cIAP1 (blue) and Xiap (green), contrasted with measured cardiac marker tnnt2 (Cardiac Troponin T) and inflammatory marker cxcl1. e ) Compiled expression timecourse of representative myeloid-related transcripts (maroon) and lymphoid transcripts (blue) from LV infarct region post-MI. ptprc (black) = hematopoietic marker gene transcript. f ) Gene Ontogeny (GO) pathway enrichment following MI identifies multiple networks requiring cIAP2. g ) NOD1 −/− mice have reduced systolic dysfunction and cardiac inflammation following MI relative to WT control mice. Control-operated mice: N = 3; MI-operated mice: N = 5. Ejection fraction: N = 4 MI-operated per group. h ) cIAP2 is expressed at lower levels, along with inflammatory genes RIPK1, IRAK4 and TRAF6, in multiple danger signaling receptor-deficient mouse models following MI. Image is representative of two similar experiments. Error bars denote Mean +/- SD; p values were calculated using one-way ANOVA with Bonferroni’s correction ( g , upper panel) or two-sided t-test ( g , lower panel).$

Journal: Nature Cardiovascular Research

Article Title: Hematopoietic expression of cIAP2 drives inflammation and heart failure after myocardial infarction

doi: 10.1038/s44161-026-00782-x

Figure Lengend Snippet: a ) and b ) Gene expression changes within infarcted left ventricle (‘infarct’) are marked at 24- and 48-hours post-MI, as assessed by hierarchical clustering and principal component analyses of the open-source GEO dataset GSE4648 . Analyses carried out using Geo2R and the open-source BART bioinformatics tool. c ) Differential gene expression patterns identified in 24-hour post-MI ventricle compared with sham control. cIAP2 (Birc3) is significantly upregulated. d ) LV infarct region gene expression timecourse of cIAP2 (maroon) and related transcripts cIAP1 (blue) and Xiap (green), contrasted with measured cardiac marker tnnt2 (Cardiac Troponin T) and inflammatory marker cxcl1. e ) Compiled expression timecourse of representative myeloid-related transcripts (maroon) and lymphoid transcripts (blue) from LV infarct region post-MI. ptprc (black) = hematopoietic marker gene transcript. f ) Gene Ontogeny (GO) pathway enrichment following MI identifies multiple networks requiring cIAP2. g ) NOD1 −/− mice have reduced systolic dysfunction and cardiac inflammation following MI relative to WT control mice. Control-operated mice: N = 3; MI-operated mice: N = 5. Ejection fraction: N = 4 MI-operated per group. h ) cIAP2 is expressed at lower levels, along with inflammatory genes RIPK1, IRAK4 and TRAF6, in multiple danger signaling receptor-deficient mouse models following MI. Image is representative of two similar experiments. Error bars denote Mean +/- SD; p values were calculated using one-way ANOVA with Bonferroni’s correction ( g , upper panel) or two-sided t-test ( g , lower panel).

Article Snippet: Left ventricular expression of gene products over a 48-hour timecourse was catalogued in the National Center for Biotechnology Information (NCBI)-curated, open-source dataset GSE4648 ( GDS2329 ) (for reference, see https://www.ncbi.nlm.nih.gov/sites/GDSbrowser?acc=GDS2329 ).

Techniques: Gene Expression, Control, Marker, Expressing