日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Malnutrition and Disability: A Retrospective Study on 2258 Adult Patients Undergoing Elective Spine Surgery

营养不良与残疾:一项对 2258 例择期脊柱手术成年患者进行的回顾性研究

Briguglio, Matteo; Campagner, Andrea; Langella, Francesco; Cecchinato, Riccardo; Damilano, Marco; Bellosta-López, Pablo; Crespi, Tiziano; De Vecchi, Elena; Latella, Marialetizia; Barone, Giuseppe; Scaramuzzo, Laura; Bassani, Roberto; Luca, Andrea; Brayda-Bruno, Marco; Wainwright, Thomas W; Middleton, Robert G; Lombardi, Giovanni; Cabitza, Federico; Banfi, Giuseppe; Berjano, Pedro

Second opinion machine learning for fast-track pathway assignment in hip and knee replacement surgery: the use of patient-reported outcome measures

利用机器学习进行髋关节和膝关节置换手术快速通道分配的第二意见:患者报告结局指标的应用

Campagner, Andrea; Milella, Frida; Banfi, Giuseppe; Cabitza, Federico

A cortico-collicular circuit for orienting to shelter during escape

逃亡过程中用于寻找庇护所的皮层-上丘回路

Dario Campagner # ,Ruben Vale # ,Yu Lin Tan ,Panagiota Iordanidou ,Oriol Pavón Arocas ,Federico Claudi ,A Vanessa Stempel ,Sepiedeh Keshavarzi ,Rasmus S Petersen ,Troy W Margrie ,Tiago Branco

Multisensory coding of angular head velocity in the retrosplenial cortex

后压部皮质的角头部速度的多感觉编码

Sepiedeh Keshavarzi, Edward F Bracey, Richard A Faville, Dario Campagner, Adam L Tyson, Stephen C Lenzi, Tiago Branco, Troy W Margrie

Innate heuristics and fast learning support escape route selection in mice

小鼠的先天启发式和快速学习能力支持其选择逃生路线。

Claudi, Federico; Campagner, Dario; Branco, Tiago

A robust and parsimonious machine learning method to predict ICU admission of COVID-19 patients

一种稳健且简洁的机器学习方法,用于预测新冠肺炎患者入住ICU的情况

Famiglini, Lorenzo; Campagner, Andrea; Carobene, Anna; Cabitza, Federico

Mice learn multi-step routes by memorizing subgoal locations

小鼠通过记忆子目标位置来学习多步骤路线。

Shamash, Philip; Olesen, Sarah F; Iordanidou, Panagiota; Campagner, Dario; Banerjee, Nabhojit; Branco, Tiago

Unity Is Intelligence: A Collective Intelligence Experiment on ECG Reading to Improve Diagnostic Performance in Cardiology

团结就是智慧:一项关于心电图判读的集体智慧实验,旨在提高心脏病学诊断性能

Ronzio, Luca; Campagner, Andrea; Cabitza, Federico; Gensini, Gian Franco

Ordinal labels in machine learning: a user-centered approach to improve data validity in medical settings

机器学习中的序数标签:一种以用户为中心的方法,用于提高医疗环境中的数据有效性

Seveso, Andrea; Campagner, Andrea; Ciucci, Davide; Cabitza, Federico

As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AI

仿佛沙子也能变成石头。我们需要新的概念和指标来探索构建可信赖人工智能的基础。

Cabitza, Federico; Campagner, Andrea; Sconfienza, Luca Maria