Predicting Dinitrogen Activation and Coupling with Carbon Dioxide and Other Small Molecules by Methyleneborane: A Combined DFT and Machine Learning Study by Feiying You (22119041)

“…Machine learning analysis suggests that increasing the HOMO–LUMO gap or the charge on the boron atom or decreasing the charge of the nitrogen atom will reduce the reaction energies. …”

Baseline characteristics of the participants. by Junichi Kushioka (12236447)

“…Although diagnosing LS using standardized charts is straightforward, the labor-intensive and time-consuming nature of the process limits its widespread implementation. To address this, we introduced a Deep Learning (DL)-based computer vision model that employs OpenPose for pose estimation and MS-G3D for spatial-temporal graph analysis. …”

Internal validation by cross-validation. by Junichi Kushioka (12236447)

“…Although diagnosing LS using standardized charts is straightforward, the labor-intensive and time-consuming nature of the process limits its widespread implementation. To address this, we introduced a Deep Learning (DL)-based computer vision model that employs OpenPose for pose estimation and MS-G3D for spatial-temporal graph analysis. …”

SHAP dependence plots with interaction coloring. by Wentao Yang (205781)

“…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”

Screening process diagram. by Wentao Yang (205781)

“…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”

SHAP waterfall plot. by Wentao Yang (205781)

“…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”

SHAP decision plot. by Wentao Yang (205781)

“…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”

LASSO regression visualization plot. by Wentao Yang (205781)

“…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”

SHAP dependence plots. by Wentao Yang (205781)

“…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”

Tertile stratified subgroup analysis. by Wentao Yang (205781)

“…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”

Arrangement of PHC facilities in a woreda NoCs. by Gizachew Tadele Tiruneh (8407686)

“…The <i>"Improve Primary Health Care Service Delivery (IPHCSD)"</i> project, implemented by JSI and Amref Health Africa since April 2022, seeks to address these gaps through a Networks of Care (NoCs) approach. This paper describes the lessons learned from implementing the NoCs approach to optimize primary health care in Ethiopia.…”

Fish hydrolysate supplementation prevents short-term and long-term spatial memory deficits and promotes the use of spatial strategies during spatial learning in D-gal mice. by Camille Mougin (19942355)

Image 1_Caffeine on the mind: EEG and cardiovascular signatures of cortical arousal revealed by wearable sensors and machine learning—a pilot study on a male group.jpeg by Shabbir Chowdhury (22246345)

“…Although systolic and diastolic BP showed a non-significant upward trend, HR decreased significantly after caffeine intake (77 ± 5.3 bpm to 72 ± 2.5 bpm, p = 0.027). …”

Image 2_A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults.jpeg by Daisu Abe (20498225)

“…In this study, we developed a machine learning model to predict the occurrence of neurological deterioration after mild TBI using information obtained on admission.…”

Image 1_A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults.jpeg by Daisu Abe (20498225)

“…In this study, we developed a machine learning model to predict the occurrence of neurological deterioration after mild TBI using information obtained on admission.…”

Table 2_A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults.docx by Daisu Abe (20498225)

“…In this study, we developed a machine learning model to predict the occurrence of neurological deterioration after mild TBI using information obtained on admission.…”

Table 3_A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults.docx by Daisu Abe (20498225)

“…In this study, we developed a machine learning model to predict the occurrence of neurological deterioration after mild TBI using information obtained on admission.…”

Table 1_A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults.docx by Daisu Abe (20498225)

“…In this study, we developed a machine learning model to predict the occurrence of neurological deterioration after mild TBI using information obtained on admission.…”

A Comparison Study of Open Source LLMs for HPC Tickets Answering by Zhao Zhang (17060598)

Residual plot for the Teamwork and collaboration variable. by Thales Guardia de Barros (22216025)