265 research outputs found
“Continuum Ansia e Depressione”. Presentazione casi clinici. (Boehringer-Ingelheim). Camogli (Genova), 17-18 aprile 2009 (co-relatori: G. Biggio, G. Cerveri, C. Mencacci, G.R. Perna, R.L. Picci, V. Rosso, R. Torta, M. Vaggi).
No full textPresentazione casi clinici
Recent developments in biomechanical data collection and processing: Probabilistic frameworks, state-space approaches and model-based techniques
No full textConsulenze in pronto soccorso e nei reparti ospedalieri
No full textIl capitolo descrive sinteticamente le competenze richieste per l'esecuzione di una consulenza psichiatrica in un reparto ospedaliero o al pronto soccorso
Main challenges on the curation of large scale datasets for pancreas segmentation using deep learning in multi-phase CT scans: Focus on cardinality, manual refinement, and annotation quality
No full textAccurate segmentation of the pancreas in computed tomography (CT) holds paramount importance in diagnostics, surgical planning, and interventions. Recent studies have proposed supervised deep-learning models for segmentation, but their efficacy relies on the quality and quantity of the training data. Most of such works employed small-scale public datasets, without proving the efficacy of generalization to external datasets. This study explored the optimization of pancreas segmentation accuracy by pinpointing the ideal dataset size, understanding resource implications, examining manual refinement impact, and assessing the influence of anatomical subregions. We present the AIMS-1300 dataset encompassing 1,300 CT scans. Its manual annotation by medical experts required 938 h. A 2.5D UNet was implemented to assess the impact of training sample size on segmentation accuracy by partitioning the original AIMS-1300 dataset into 11 smaller subsets of progressively increasing numerosity. The findings revealed that training sets exceeding 440 CTs did not lead to better segmentation performance. In contrast, nnU-Net and UNet with Attention Gate reached a plateau for 585 CTs. Tests on generalization on the publicly available AMOS-CT dataset confirmed this outcome. As the size of the partition of the AIMS-1300 training set increases, the number of error slices decreases, reaching a minimum with 730 and 440 CTs, for AIMS-1300 and AMOS-CT datasets, respectively. Segmentation metrics on the AIMS-1300 and AMOS-CT datasets improved more on the head than the body and tail of the pancreas as the dataset size increased. By carefully considering the task and the characteristics of the available data, researchers can develop deep learning models without sacrificing performance even with limited data. This could accelerate developing and deploying artificial intelligence tools for pancreas surgery and other surgical data science applications
Defining Effective Strategies to Prevent Post-Traumatic Stress in Healthcare Emergency Workers Facing the COVID-19 Pandemic in Italy
No full textThe COVID-19 pandemic exponentially increased stress on healthcare workers (HCWs), overwhelming their physical and psychological working capacities. The hospital epicenter of the Italian outbreak promptly provided supportive strategies to prevent PTSD: risk factors and feedbacks in the acute phase are debated
Base-promoted Conia-ene cyclization of propargyl amides
No full textWe report a tBuOK-promoted synthesis of 1,3-dihydro-2H-pyrrol-2-one and 4-methylenepyrrolidin-2-one systems via Conia-ene like intramolecular cyclization. The method features extremely short reaction times (5 min) and mild reaction conditions (rt), enabling the trapping of a propargyl unit by an amide enolate. An intriguing anionic chain mechanism is at work, which can trigger the isomerization of an exo-alkene giving access to the otherwise elusive endo-product
Derivation of centers and axes of rotation for wrist and fingers in a hand kinematic model: methods and reliability results
No full textIn the field of 3D reconstruction of human motion from video, model-based techniques have been proposed to increase the estimation accuracy and the degree of automation. The feasibility of this approach is strictly connected with the adopted biomechanical model. Particularly, the representation of the kinematic chain and the assessment of the corresponding parameters play a relevant role for the success of the motion assessment. In this paper, the focus is on the determination of the kinematic parameters of a general hand skeleton model using surface measurements. A novel method that integrates nonrigid sphere fitting and evolutionary optimization is proposed to estimate the centers and the functional axes of rotation of the skeletal joints. The reliability of the technique is tested using real movement data and simulated motions with known ground truth 3D measurement noise and different ranges of motion (RoM). With respect to standard nonrigid sphere fitting techniques, the proposed method performs 10-50% better in the best condition (very low noise and wide RoM) and over 100% better with physiological artifacts and RoM. Repeatability in the range of a couple of millimeters, on the localization of the centers of rotation, and in the range of one degree, on the axis directions is obtained from real data experiments
GAAS: Gene Array Analyzer Software for management, analysis and visualization of gene expression data
No full textSummary: GAAS, Gene Array Analyzer Software supports multi-user efficient management and suitable analyses of large amounts of gene expression data across replicated experiments. Its management framework handles input data generated by different technologies. A multi-user environment allows each user to store his/her own data visualization scheme, analysis parameters used, values and formats of the output data. The analysis engine performs: background and spot quality evaluation, data normalization, differential gene expression analyses in single and multiple replica experiments. Results of expression profiles can be interactively navigated through graphical interfaces and stored into output databases.
Availability: http://www.medinfopoli.polimi.it/GAAS/
Contact: [email protected]
Supplementary information: http://www.medinfopoli.polimi.it/GAAS
In-vivo estimation of the kinematic parameters of the trapezio-metacarpal joint using surface markers
No full text- …
