Alle Publikationen zum Thema Maschinelles Lernen, Neuronale Netze, und Deep Learning
2022
Ming DK,
Hernandez B,
Sangkaew S,
Vuong NL,
Lam PK,
Nguyet NM,
Tam DTH,
Trung DT,
Tien NTH,
Tuan NM,
Chau NVV,
Tam CT,
Chanh HQ,
Trieu HT,
Simmons CP,
Wills B,
Georgiou P,
Holmes AH,
Yacoub S,
Vietnam ICU Translational Applications Laboratory (VITAL) investigators} {.
Applied Machine Learning for the Risk-Stratification and Clinical Decision Support of Hospitalised Patients with Dengue in Vietnam.
PLOS Digital Health.
2022 Jan.;
1(1):e0000005.
[DOI]
Lu P,
Ghiasi S,
Hagenah J,
Hai HB,
Hao NV,
Khanh PNQ,
Khoa LDV,
VC,
Thwaites L,
Clifton DA,
Zhu T.
Classification of Tetanus Severity in Intensive-Care Settings for Low-Income Countries Using Wearable Sensing.
Sensors.
2022 Aug.;
22(17):6554.
[DOI]
2021
Ferretti A,
Ienca M,
Sheehan M,
Blasimme A,
Dove ES,
Farsides B,
Friesen P,
Kahn J,
Karlen W,
Kleist P,
Liao SM,
Nebeker C,
Samuel G,
Shabani M,
Rivas Velarde M,
Vayena E.
Ethics review of big data research: What should stay and what should be reformed?.
BMC Medical Ethics.
2021 Dec.;
22(1):51.
[DOI]
[File]
2020
2019
Brogli L,
Karlen W.
A Review of Deep Learning for Automatic Sleep Stage Scoring. In:
International Conference on Advanced Sleep Modulation Technologies.
Monte Verita, Ascona, Switzerland:
2019.
Schwab P,
Karlen W.
CXPlain: Causal Explanations for Model Interpretation under Uncertainty}. In:
Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019.
Vancouver, CA:
2019.
p. accepted.
[File]
Rodriguez Orefice H,
Scebba G,
Catanzaro S,
Berli M,
Karlen W.
Wound image segmentation with deep neural networks. In:
Annual Meeting of the Swiss Society for Biomedical Engineering (SSBE) 2019.
2019.
2018
Schwab P,
Linhardt L,
Karlen W.
Perfect Match: A Simple Method for Learning Representations For Counterfactual Inference With Neural Networks.
ArXiv Preprint.
2018;
[File]
2017
Schwab P,
Khashkhashi Moghaddam MA,
Karlen W.
Automated Extraction of Digital Biomarkers for Parkinson ' s Disease. In:
10th Annual RECOMB/ISCB Conference on Regulatory & Systems Genomics with DREAM Challenges.
New York, USA:
Sage Bionetworks;
2017.
[File]
2016
Luca VD,
Jaggi M,
Karlen W,
Keller E.
Temporal prediction of cerebral hypoxia in neurointensive care patients: a feasibility study. In:
International Symposium on Intracranial Pressure and Neuromonitoring.
2016.
p. 86--87.
2015
Jaggi M,
Karlen W,
Keller E.
Forecasting intracranial hypertension using waveform and time series features. In:
Vasospasm 2015 - 13th International Conference on Neurovascular Events after Subarachnoid Hemorrhage.
Nagano, Japan:
2015.
Jaggi M,
Luca VD,
Karlen W.
Predicting intracranial pressure elevation using multiparameter summaries of physiological channels. In:
Annual Meeting of the Swiss Society for Biomedical Engineering (SSBE).
Neuchatel, Switzerland:
2015.
2009
Karlen W,
Mattiussi C,
Floreano D.
Sleep and Wake Classification With ECG and Respiratory Effort Signals.
IEEE Transactions on Biomedical Circuits and Systems.
2009;
3(2):71--8.
[DOI]
2008
2007
Karlen W,
Mattiussi C,
Floreano D.
Human Sleep/Wake Classification. In:
BMES Annual Chapter Conference.
Lausanne, CH:
2007.