Image 2_Using deep learning to detect upper limb compensation in individuals post-stroke using consumer-grade webcams—A feasibility study.jpeg by Tim Unger (20457145)

“…This study investigates whether a single webcam, combined with human pose estimation and deep learning algorithms, can automatically detect compensatory movements in persons with stroke performing a drinking task. …”

Image 1_Using deep learning to detect upper limb compensation in individuals post-stroke using consumer-grade webcams—A feasibility study.jpeg by Tim Unger (20457145)

“…This study investigates whether a single webcam, combined with human pose estimation and deep learning algorithms, can automatically detect compensatory movements in persons with stroke performing a drinking task. …”

Image 3_Using deep learning to detect upper limb compensation in individuals post-stroke using consumer-grade webcams—A feasibility study.jpeg by Tim Unger (20457145)

“…This study investigates whether a single webcam, combined with human pose estimation and deep learning algorithms, can automatically detect compensatory movements in persons with stroke performing a drinking task. …”

Table_1_Development and validation of a multivariable nomogram predictive of hepatitis B e antigen seroconversion after pregnancy in hepatitis B virus-infected mothers.DOCX by Wenting Zhong (11460046)

“…The postpartum period may be an opportune moment for achieving hepatitis B e antigen (HBeAg) seroconversion earlier with constant NAs therapy due to the restoration of immune function after delivery. We investigated prenatal and pregnant factors associated with HBeAg seroconversion after pregnancy and developed a nomogram to predict HBeAg seroconversion rates, aiding decision-making for optimal management in women.…”

Selection and analysis of characteristic genes for non-obstructive azoospermia (NOA). by Qiang Ling (11415101)

Feature mapping for vowel-e. by Gaurav Datkhile (22662871)

“…This study investigates using OpenSMILE features for COVID-19 detection using vowel speech sounds /a/, /e/, and /o/ from the COSWARA dataset. OpenSMILE facilitates the extraction of audio and functional features, which are then classified using various machine learning algorithms. …”

Feature mapping for vowel-o. by Gaurav Datkhile (22662871)

“…This study investigates using OpenSMILE features for COVID-19 detection using vowel speech sounds /a/, /e/, and /o/ from the COSWARA dataset. OpenSMILE facilitates the extraction of audio and functional features, which are then classified using various machine learning algorithms. …”

Confusion Matrix for result analysis. by Gaurav Datkhile (22662871)

“…This study investigates using OpenSMILE features for COVID-19 detection using vowel speech sounds /a/, /e/, and /o/ from the COSWARA dataset. OpenSMILE facilitates the extraction of audio and functional features, which are then classified using various machine learning algorithms. …”

System block diagram. by Gaurav Datkhile (22662871)

“…This study investigates using OpenSMILE features for COVID-19 detection using vowel speech sounds /a/, /e/, and /o/ from the COSWARA dataset. OpenSMILE facilitates the extraction of audio and functional features, which are then classified using various machine learning algorithms. …”

Evaluation of the relationship between KLF4 expression and cancer-associated fibroblast (CAF) infiltration. by Shoukai Yu (5003270)

The immune microenvironment association of CENPA in cancers. by Hengrui Liu (2059750)

SHAP values for co-occupying PRC1 (RING1B) and PRC2 (SUZ12) components and their catalytic marks. by Kashyap Chhatbar (9515350)

SHAP values for H3K4me3, co-occupying PRC1 (RING1B) and PRC2 (SUZ12) components and their catalytic marks across multiple time points following RING1B degradation. by Kashyap Chhatbar (9515350)

Symbolic regression flow diagram. by Mengze Zhang (19422095)

Data Sheet 1_Identification of novel molecular subtypes and construction of a prognostic signature via multi-omics analysis and machine learning in lung adenocarcinoma.docx by Ke Ma (260231)

“…A multi-omics and machine learning-driven prognostic signature (MO-MLPS) was constructed in The Cancer Genome Atlas (TCGA) LUAD dataset using ten machine learning algorithms and subsequently validated across six independent datasets from the Gene Expression Omnibus (GEO) database. …”

Table 3_Identification and validation of glycolysis-related diagnostic signatures in diabetic nephropathy: a study based on integrative machine learning and single-cell sequence.xl... by Xiaoyin Wu (15279940)

“…</p>Results<p>Through the 108 combinations of machine learning algorithms, we selected 12 diagnostic signatures, including CD163, CYBB, ELF3, FCN1, PROM1, GPR65, LCN2, LTF, S100A4, SOX4, TGFB1 and TNFAIP8. …”

Table 2_Identification and validation of glycolysis-related diagnostic signatures in diabetic nephropathy: a study based on integrative machine learning and single-cell sequence.xl... by Xiaoyin Wu (15279940)

“…</p>Results<p>Through the 108 combinations of machine learning algorithms, we selected 12 diagnostic signatures, including CD163, CYBB, ELF3, FCN1, PROM1, GPR65, LCN2, LTF, S100A4, SOX4, TGFB1 and TNFAIP8. …”

Table 5_Identification and validation of glycolysis-related diagnostic signatures in diabetic nephropathy: a study based on integrative machine learning and single-cell sequence.xl... by Xiaoyin Wu (15279940)

“…</p>Results<p>Through the 108 combinations of machine learning algorithms, we selected 12 diagnostic signatures, including CD163, CYBB, ELF3, FCN1, PROM1, GPR65, LCN2, LTF, S100A4, SOX4, TGFB1 and TNFAIP8. …”

Table 1_Shared genetic architecture between COVID-19 and irritable bowel syndrome: a large-scale genome-wide cross-trait analysis.xlsx by Xianqiang Liu (228089)

“…</p>Results<p>We found a positive genetic correlation between COVID-19 infection, COVID-19 hospitalization, and IBS. …”

Table 4_Identification and validation of glycolysis-related diagnostic signatures in diabetic nephropathy: a study based on integrative machine learning and single-cell sequence.xl... by Xiaoyin Wu (15279940)

“…</p>Results<p>Through the 108 combinations of machine learning algorithms, we selected 12 diagnostic signatures, including CD163, CYBB, ELF3, FCN1, PROM1, GPR65, LCN2, LTF, S100A4, SOX4, TGFB1 and TNFAIP8. …”