Image 2_Hemoglobin glycation index and all-cause mortality in adults: insights from a decade-long prospective cohort study.tif by Yue-Yang Zhang (14258160)

“…After COX regression, restricted cubic spline analysis, and subgroup analyses, it was found that a significant increase or decrease in HGI adversely affected long-term survival.…”

Image 1_Hemoglobin glycation index and all-cause mortality in adults: insights from a decade-long prospective cohort study.tif by Yue-Yang Zhang (14258160)

“…After COX regression, restricted cubic spline analysis, and subgroup analyses, it was found that a significant increase or decrease in HGI adversely affected long-term survival.…”

Vertebral cancellous tissueμCT parameters are not significantly affected by aging from 16 to 21 weeks, housing type, or microgravity. by Rukmani Cahill (20939813)

“…Data shown are the mean ±  standard deviation with a scatter plot (ns: non-significant). (G) μCT volumetric reconstructions of a representative sample from each group show a slight decrease in bone parameters from FL mice, which are not deemed significant by statistical testing.…”

Preference for the EIA – conjoint results. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Marginal means – Pooled across scenarios. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Sample attribute table. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Subgroup analysis – Political affiliation. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Sample scenario description. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

AMCEs – Pooled across scenarios. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Methodological flowchart. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Preference for the EIA vs. ETA across scenarios. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Statistically Significant Results for Heart Rate Variability (HRV) Indices for High and Low Authority Groups. by David Vagni (8060432)

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Statistically Significant Results for Heart Rate Variability (HRV) Indices for High and Low Clarity Groups. by David Vagni (8060432)

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A mathematical model of PIF4 autoregulation captures the experimental observations of hypocotyl growth and promoter activity. by Sreya Das (20531295)

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Blood Pressure and LDL-C During Follow-up. by Karl Ingard (22582091)

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Baseline Characteristics of Included Patients. by Karl Ingard (22582091)

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Impaired development of the brain and iBAT of rarely alive adult <i>aP2-Drp1</i>^f/f mice. by Yuta Ibayashi (20404811)

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HE staining results of cartilage tissue in different groups of rat PTOA (A: normal group, B: mild PTOA group, C: severe PTOA group). by Peng-fei Han (694841)

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Characteristics of the included studies. by Si He (3236646)

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Extracted data and used for analysis. by Si He (3236646)

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