Image 5_A machine learning model based on emergency clinical data predicting 3-day in-hospital mortality for stroke and trauma patients.jpeg by Xu Chen (432759)

“…This approach, which incorporates emergency data, holds promise for assisting decision-making in clinical practice, thereby improving patient outcomes.…”

Image 1_A machine learning model based on emergency clinical data predicting 3-day in-hospital mortality for stroke and trauma patients.tif by Xu Chen (432759)

“…This approach, which incorporates emergency data, holds promise for assisting decision-making in clinical practice, thereby improving patient outcomes.…”

Image 2_A machine learning model based on emergency clinical data predicting 3-day in-hospital mortality for stroke and trauma patients.tif by Xu Chen (432759)

“…This approach, which incorporates emergency data, holds promise for assisting decision-making in clinical practice, thereby improving patient outcomes.…”

Image 4_A machine learning model based on emergency clinical data predicting 3-day in-hospital mortality for stroke and trauma patients.tif by Xu Chen (432759)

“…This approach, which incorporates emergency data, holds promise for assisting decision-making in clinical practice, thereby improving patient outcomes.…”

Image 3_A machine learning model based on emergency clinical data predicting 3-day in-hospital mortality for stroke and trauma patients.tif by Xu Chen (432759)

“…This approach, which incorporates emergency data, holds promise for assisting decision-making in clinical practice, thereby improving patient outcomes.…”

Table 1_A machine learning model based on emergency clinical data predicting 3-day in-hospital mortality for stroke and trauma patients.docx by Xu Chen (432759)

“…This approach, which incorporates emergency data, holds promise for assisting decision-making in clinical practice, thereby improving patient outcomes.…”

Morpheus: A fragment-based algorithm to predict metamorphic behaviour in proteins across proteomes by Vijay Subramanian (20718933)

Algorithm and its parameter settings. by Lin Li (28817)

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Personnel requirements per fokontany for proCCM programs. by Mauricianot Randriamihaja (9091488)

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Personnel requirements per fokontany for mass distribution campaigns. by Mauricianot Randriamihaja (9091488)

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Number of CHWs required for proCCM programs in Ifanadiana District under a range of program design scenarios. by Mauricianot Randriamihaja (9091488)

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Spatial distribution of personnel-days requirements per fokontany to deliver community health interventions in Ifanadiana district. by Mauricianot Randriamihaja (9091488)

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Routing optimization tool implemented as an interactive dashboard for use by community health programs in Ifanadiana District. by Mauricianot Randriamihaja (9091488)

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Model assumptions for mass distribution campaign and proCCM intervention scenarios. by Mauricianot Randriamihaja (9091488)

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Illustrative example of optimal daily itineraries for two CHWs to visit every household in their catchment. by Mauricianot Randriamihaja (9091488)

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Performance of algorithms outside the training species. by Sven B. Gould (12237287)

Supporting data for “Developing algorithms to optimize recommender system for self-regulated learning promotion in online contexts: a design-based study” by Long Zhang (11129139)

Data_Sheet_1_Development and pilot evaluation of an evidence-based algorithm for MASLD (formerly NAFLD) management in primary care in Europe.docx by Marilena Anastasaki (4453894)

“…</p>Methods<p>An international multidisciplinary panel of experts oversaw pathway development, which was designed as a two-step algorithm with defined and sequenced tasks. …”

Accuracy verification of big data diagnosis and early warning algorithm. by Hao-yang Li (17815508)

The results of bug reports classification by the MNB algorithm. by Mohammadreza Namdar (22439057)