Data and percentage of optimal performance of the 3 methods. by Wenyu Chen (9135516)

Seamless integration of legacy robotic systems into a self-driving laboratory via NIMO: a case study on liquid handler automation by Ryo Tamura (1957942)

Development of a machine learning prognostic model for early prediction of scrub typhus progression at hospital admission based on clinical and laboratory features by Youguang Lu (12526579)

“…Eighteen objective clinical and laboratory features collected at admission were screened using various feature selection algorithms, and used to construct models based on six machine learning algorithms.…”

S1 File - by Michael Bonert (3751348)

S2 File - by Michael Bonert (3751348)

Clinical history. by Michael Bonert (3751348)

Neuroanatomical site overlap. by Michael Bonert (3751348)

Image_1_Development and Validation of a Predictive Model for Severe COVID-19: A Case-Control Study in China.TIFF by Zirui Meng (10671261)

Image_2_Development and Validation of a Predictive Model for Severe COVID-19: A Case-Control Study in China.TIFF by Zirui Meng (10671261)

Image_3_Development and Validation of a Predictive Model for Severe COVID-19: A Case-Control Study in China.TIF by Zirui Meng (10671261)

Local alignment regime and symbols.pdf by Paul A. Gagniuc (1818325)

Diversity and specificity of lipid patterns in basal soil food web resources by Jakob Kühn (7288466)

“…In marine environments, multivariate optimization models (Quantitative Fatty Acid Signature Analysis) and Bayesian approaches (source-tracking algorithm) were established to predict the proportion of predator diets using lipids as tracers. …”

Data Sheet 1_Interpretable machine-learning-based prediction of postpartum haemorrhage in normal vaginal births in Shanghai, China.pdf by Xiao Yao (135696)

“…</p>Aim<p>To develop a predictive model for postpartum haemorrhage in vaginal births based on machine-learning algorithms.</p>Methods<p>We selected pregnant women who gave birth vaginally at a tertiary-level obstetrics and gynaecology hospital in Shanghai, China, from July 2023 to August 2024. …”

Data_Sheet_1_Early Prediction of Cardiogenic Shock Using Machine Learning.PDF by Yale Chang (11701611)

“…Patients who develop CS may have previous cardiac history, but that may not always be the case, adding to the challenges in optimally identifying and managing these patients. …”

Data_Sheet_1_Utilization of a Meningitis/Encephalitis PCR panel at the University Hospital Basel – a retrospective study to develop a diagnostic decision rule.DOCX by Andrea Erba (15420463)

“…Our results highlight the need for diagnostic-stewardship interventions when utilizing this assay by implementing a stepwise approach based on a limited number of clinical and laboratory features. …”

Table 1_Risk prediction for gastrointestinal bleeding in pediatric Henoch-Schönlein purpura using an interpretable transformer model.doc by Gahao Chen (21688843)

“…GI complications were stratified into three severity tiers: 1) no complications, 2) abdominal pain without bleeding), and 3) documented rectal bleeding or hemorrhage, based on standardized diagnostic criteria. Five machine learning algorithms (Random Forest, XGBoost, LightGBM, CatBoost, and TabPFN-V2) were optimized through nested cross-validation. …”

Data_Sheet_1_Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU.docx by Elham Jamshidi (11013993)

“…<p>Rationale: Given the expanding number of COVID-19 cases and the potential for new waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies.…”

Table_1_iMAGING: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope.DOCX by Carles Rubio Maturana (17448078)

“…</p>Conclusion<p>The coalescence of the fully-automated system via auto-focus and slide movements and the autonomous detection of Plasmodium parasites in digital images with a smartphone software and AI algorithms confers the prototype the optimal features to join the global effort against malaria, neglected tropical diseases and other infectious diseases.…”

Image_1_iMAGING: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope.TIFF by Carles Rubio Maturana (17448078)

“…</p>Conclusion<p>The coalescence of the fully-automated system via auto-focus and slide movements and the autonomous detection of Plasmodium parasites in digital images with a smartphone software and AI algorithms confers the prototype the optimal features to join the global effort against malaria, neglected tropical diseases and other infectious diseases.…”

Image_2_iMAGING: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope.TIFF by Carles Rubio Maturana (17448078)

“…</p>Conclusion<p>The coalescence of the fully-automated system via auto-focus and slide movements and the autonomous detection of Plasmodium parasites in digital images with a smartphone software and AI algorithms confers the prototype the optimal features to join the global effort against malaria, neglected tropical diseases and other infectious diseases.…”