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Book ; Online: Simmel: A Ruína

Fortuna, Carlos / Ribeiro, António Sousa

2019

Abstract: It presents the centenary essay of Simmel The Ruin, in a version of 1919 although the text originally appeared in 1911, and discusses the authors approach to aesthetics and the meaning of classical ruin. At the same time, the (post)industrial ruins are ... ...

Abstract	It presents the centenary essay of Simmel The Ruin, in a version of 1919 although the text originally appeared in 1911, and discusses the authors approach to aesthetics and the meaning of classical ruin. At the same time, the (post)industrial ruins are disallowed, which allows questions about the current hypotheses of the German philosopher. The ruin of Simmel argues about the conflict of nature with the spirit and the way the revolt of nature that generates the ruin, also produces peace and temperance. The treatment of Simmel presents general traces of the romantic assessment of ruin and is not immediate its approximation to the context of contemporary ruin resulting from human action (Incuria, degradation and wars). It is this industrial (post) ruin that is brought to the comparison and that by marking two consecrated cases of contemporary urban ruin - Aleppo and Detroit - makes highlighting the aesthetic order of decay in which the contrast with the ruin of Simmel gains sense and actuality
Size	1 electronic resource (66 pages)
Publisher	Coimbra University Press
Document type	Book ; Online
Note	Ruin, aesthetics and meaning, classic ruin, (post)industrial ruin, conflict of nature with the spirit, contemporary ruin ; Open Access
HBZ-ID	HT020589322
ISBN	9789892618227 ; 989261822X
DOI	10.14195/978-989-26-1823-4
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Book ; Online: O Império da Vontade e a raiz cristã da descristianização

Ribeiro, António Vitor

2017

Abstract: O principal objectivo deste livro é determinar as bases do processo de secularização e laicização da sociedade portuguesa e tentar entender se o processo português é generalizável aos outros países da Europa Ocidental. A análise parte do processo de ... ...

Abstract	O principal objectivo deste livro é determinar as bases do processo de secularização e laicização da sociedade portuguesa e tentar entender se o processo português é generalizável aos outros países da Europa Ocidental. A análise parte do processo de massificação da literatura de espiritualidade, que teve início em França no início do século XVII e conheceu prolongamentos em Portugal na segunda metade do século. Este processo levou a uma "secularização da devoção" e ao desenvolvimento de uma epistemologia, primeiro, e a uma psicologia, depois. Pretende-se demonstrar a forma como o iluminismo português, encarnado pelo Marquês de Pombal, veiculava uma visão do homem que se fundava na profunda introspecção resultante desse processo. Procura-se, igualmente, demonstrar a emergência de um partido agostiniano e anti-jesuítico em Portugal na segunda metade do século XVII, e que Pombal utilizou como base social crítica para o seu processo de reformas sociais. Trata-se de uma forma de abordar a questão da secularização que está nos antípodas da tese oficial de uma retirada progressiva de Deus do seio da sociedade humana. Paradoxalmente, a gradual emancipação da razão humana pode ter sido potenciada pela acção daqueles que mais a desprezavam
Keywords	Religion (General)
Size	1 electronic resource (420 p.)
Publisher	Coimbra University Press
Document type	Book ; Online
Note	Portuguese ; Open Access
HBZ-ID	HT020103008
ISBN	9789892613451 ; 9892613457
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: On Merging Feature Engineering and Deep Learning for Diagnosis, Risk Prediction and Age Estimation Based on the 12-Lead ECG.

Zvuloni, Eran / Read, Jesse / Ribeiro, Antonio H / Ribeiro, Antonio Luiz P / Behar, Joachim A

IEEE transactions on bio-medical engineering

2023 Volume 70, Issue 7, Page(s) 2227–2236

Abstract: Objective: Over the past few years, deep learning (DL) has been used extensively in research for 12-lead electrocardiogram (ECG) analysis. However, it is unclear whether the explicit or implicit claims made on DL superiority to the more classical ... ...

Abstract	Objective: Over the past few years, deep learning (DL) has been used extensively in research for 12-lead electrocardiogram (ECG) analysis. However, it is unclear whether the explicit or implicit claims made on DL superiority to the more classical feature engineering (FE) approaches, based on domain knowledge, hold. In addition, it remains unclear whether combining DL with FE may improve performance over a single modality. Methods: To address these research gaps and in-line with recent major experiments, we revisited three tasks: cardiac arrhythmia diagnosis (multiclass-multilabel classification), atrial fibrillation risk prediction (binary classification), and age estimation (regression). We used an overall dataset of 2.3M 12-lead ECG recordings to train the following models for each task: i) a random forest taking FE as input; ii) an end-to-end DL model; and iii) a merged model of FE+DL. Results: FE yielded comparable results to DL while necessitating significantly less data for the two classification tasks. DL outperformed FE for the regression task. For all tasks, merging FE with DL did not improve performance over DL alone. These findings were confirmed on the additional PTB-XL dataset. Conclusion: We found that for traditional 12-lead ECG based diagnosis tasks, DL did not yield a meaningful improvement over FE, while it improved significantly the nontraditional regression task. We also found that combining FE with DL did not improve over DL alone, which suggests that the FE was redundant with the features learned by DL. Significance: Our findings provides important recommendations on 12-lead ECG based machine learning strategy and data regime to choose for a given task. When looking at maximizing performance as the end goal, if the task is nontraditional and a large dataset is available then DL is preferable. If the task is a classical one and/or a small dataset is available then a FE approach may be the better choice.
MeSH term(s)	Humans ; Deep Learning ; Atrial Fibrillation ; Machine Learning ; Electrocardiography/methods
Language	English
Publishing date	2023-06-19
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	160429-6
ISSN	1558-2531 ; 0018-9294
ISSN (online)	1558-2531
ISSN	0018-9294
DOI	10.1109/TBME.2023.3239527
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Primary Lateral Sclerosis: Can Rocuronium Be an Option?

Palha Ribeiro, Antonio / Tomas, Ana Sofia / Oliveira, Carla

Cureus

2023 Volume 15, Issue 3, Page(s) e35773

Abstract: Primary lateral sclerosis (PLS) is a neurodegenerative motor neuron disorder that is characterized by corticospinal and corticobulbar dysfunction. In this disease, muscle relaxants in general anesthesia should be used with extreme caution. A 67-year-old ... ...

Abstract	Primary lateral sclerosis (PLS) is a neurodegenerative motor neuron disorder that is characterized by corticospinal and corticobulbar dysfunction. In this disease, muscle relaxants in general anesthesia should be used with extreme caution. A 67-year-old woman with a history of PLS was scheduled for laparoscopic gastrostomy due to long-term dysphagia. In the preoperative assessment, she presented a tetrapyramidal syndrome with generalized muscle weakness. A priming dose of 5 mg of rocuronium was administered and the train-of-four (TOF) ratio (T4/T1) after 60 seconds was 70% so induction was followed with fentanyl, propofol, and additional 40 mg of rocuronium. After 90 seconds when T1 was lost, the patient was intubated. During surgery, the TOF ratio increased progressively until 65%, 22 minutes after a final bolus of 10 mg of rocuronium. Prior to emergence, 150 mg of sugammadex was given and neuromuscular block reversal was evidenced with a TOF ratio > 90%. As it was decided to perform the surgery laparoscopically, general anesthesia with a neuromuscular blockade was necessary. Since it is reported that patients with motor neuron diseases show an increased sensibility to non-depolarizing muscle relaxants (NDMR), these agents should be used cautiously. Adversely to what studies document, no augmented responsiveness was shown in TOF monitoring, so the standard dose of 0.6 mg/kg of rocuronium was safely given. A final bolus of NDMR was administered after 54 minutes, demonstrating a similar pharmacokinetics profile in terms of duration of action as reported in several studies (45-70 minutes). In addition, a full and rapid neuromuscular blockade recovery with 2 mg/kg of sugammadex was seen, as previously demonstrated in a case series.
Language	English
Publishing date	2023-03-05
Publishing country	United States
Document type	Case Reports
ZDB-ID	2747273-5
ISSN	2168-8184
ISSN	2168-8184
DOI	10.7759/cureus.35773
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Increasing patient access to spirometry in the Unified Health System in Brazil: no longer a dream but a near reality.

Corrêa, Ricardo Amorim / Mancuzo, Eliane Viana / Rezende, Camila Farnese / Ribeiro, Antônio Luiz Pinho

Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia

2024 Volume 49, Issue 6, Page(s) e20230384

MeSH term(s)	Humans ; Brazil ; Spirometry ; Health Services Accessibility
Language	Portuguese
Publishing date	2024-01-15
Publishing country	Brazil
Document type	Editorial ; Research Support, Non-U.S. Gov't
ZDB-ID	2223157-2
ISSN	1806-3756 ; 1806-3713
ISSN (online)	1806-3756
ISSN	1806-3713
DOI	10.36416/1806-3756/e20230384
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Heart age gap estimated by explainable advanced electrocardiography is associated with cardiovascular risk factors and survival.

Lindow, Thomas / Maanja, Maren / Schelbert, Erik B / Ribeiro, Antônio H / Ribeiro, Antonio Luiz P / Schlegel, Todd T / Ugander, Martin

European heart journal. Digital health

2023 Volume 4, Issue 5, Page(s) 384–392

Abstract: Aims: Deep neural network artificial intelligence (DNN-AI)-based Heart Age estimations have been presented and used to show that the difference between an electrocardiogram (ECG)-estimated Heart Age and chronological age is associated with prognosis. An ...

Abstract	Aims: Deep neural network artificial intelligence (DNN-AI)-based Heart Age estimations have been presented and used to show that the difference between an electrocardiogram (ECG)-estimated Heart Age and chronological age is associated with prognosis. An accurate ECG Heart Age, without DNNs, has been developed using explainable advanced ECG (A-ECG) methods. We aimed to evaluate the prognostic value of the explainable A-ECG Heart Age and compare its performance to a DNN-AI Heart Age. Methods and results: Both A-ECG and DNN-AI Heart Age were applied to patients who had undergone clinical cardiovascular magnetic resonance imaging. The association between A-ECG or DNN-AI Heart Age Gap and cardiovascular risk factors was evaluated using logistic regression. The association between Heart Age Gaps and death or heart failure (HF) hospitalization was evaluated using Cox regression adjusted for clinical covariates/comorbidities. Among patients [ Conclusion: A-ECG Heart Age Gap is associated with cardiovascular risk factors and HF hospitalization or death. Explainable A-ECG Heart Age Gap has the potential for improving clinical adoption and prognostic performance compared with existing DNN-AI-type methods.
Language	English
Publishing date	2023-07-25
Publishing country	England
Document type	Journal Article
ISSN	2634-3916
ISSN (online)	2634-3916
DOI	10.1093/ehjdh/ztad045
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Association of lifestyle with deep learning predicted electrocardiographic age.

Zhang, Cuili / Miao, Xiao / Wang, Biqi / Thomas, Robert J / Ribeiro, Antônio H / Brant, Luisa C C / Ribeiro, Antonio L P / Lin, Honghuang

Frontiers in cardiovascular medicine

2023 Volume 10, Page(s) 1160091

Abstract: Background: People age at different rates. Biological age is a risk factor for many chronic diseases independent of chronological age. A good lifestyle is known to improve overall health, but its association with biological age is unclear.: Methods: ... ...

Abstract	Background: People age at different rates. Biological age is a risk factor for many chronic diseases independent of chronological age. A good lifestyle is known to improve overall health, but its association with biological age is unclear. Methods: This study included participants from the UK Biobank who had undergone 12-lead resting electrocardiography (ECG). Biological age was estimated by a deep learning model (defined as ECG-age), and the difference between ECG-age and chronological age was defined as Δage. Participants were further categorized into an ideal (score 4), intermediate (scores 2 and 3) or unfavorable lifestyle (score 0 or 1). Four lifestyle factors were investigated, including diet, alcohol consumption, physical activity, and smoking. Linear regression models were used to examine the association between lifestyle factors and Δage, and the models were adjusted for sex and chronological age. Results: This study included 44,094 individuals (mean age 64 ± 8, 51.4% females). A significant correlation was observed between predicted biological age and chronological age (correlation coefficient = 0.54, Conclusion: In this large contemporary population, a strong association was observed between all four studied healthy lifestyle factors and deaccelerated aging. Our study underscores the importance of a healthy lifestyle to reduce the burden of aging-related diseases.
Language	English
Publishing date	2023-04-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2781496-8
ISSN	2297-055X
ISSN	2297-055X
DOI	10.3389/fcvm.2023.1160091
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Article ; Online: End-to-end risk prediction of atrial fibrillation from the 12-Lead ECG by deep neural networks.

Habineza, Theogene / Ribeiro, Antônio H / Gedon, Daniel / Behar, Joachim A / Ribeiro, Antonio Luiz P / Schön, Thomas B

Journal of electrocardiology

2023 Volume 81, Page(s) 193–200

Abstract: Background: Atrial fibrillation (AF) is one of the most common cardiac arrhythmias that affects millions of people each year worldwide and it is closely linked to increased risk of cardiovas- cular diseases such as stroke and heart failure. Machine ... ...

Abstract	Background: Atrial fibrillation (AF) is one of the most common cardiac arrhythmias that affects millions of people each year worldwide and it is closely linked to increased risk of cardiovas- cular diseases such as stroke and heart failure. Machine learning methods have shown promising results in evaluating the risk of developing atrial fibrillation from the electrocardiogram. We aim to develop and evaluate one such algorithm on a large CODE dataset collected in Brazil. Methods: We used the CODE cohort to develop and test a model for AF risk prediction for individual patients from the raw ECG recordings without the use of additional digital biomarkers. The cohort is a collection of ECG recordings and annotations by the Telehealth Network of Minas Gerais, in Brazil. A convolutional neural network based on a residual network architecture was implemented to produce class probabilities for the classification of AF. The probabilities were used to develop a Cox proportional hazards model and a Kaplan-Meier model to carry out survival analysis. Hence, our model is able to perform risk prediction for the development of AF in patients without the condition. Results: The deep neural network model identified patients without indication of AF in the presented ECG but who will develop AF in the future with an AUC score of 0.845. From our survival model, we obtain that patients in the high-risk group (i.e. with the probability of a future AF case being >0.7) are 50% more likely to develop AF within 40 weeks, while patients belonging to the minimal-risk group (i.e. with the probability of a future AF case being less than or equal to 0.1) have >85% chance of remaining AF free up until after seven years. Conclusion: We developed and validated a model for AF risk prediction. If applied in clinical practice, the model possesses the potential of providing valuable and useful information in decision- making and patient management processes.
MeSH term(s)	Humans ; Atrial Fibrillation/diagnosis ; Electrocardiography/methods ; Neural Networks, Computer ; Algorithms ; Machine Learning
Language	English
Publishing date	2023-09-25
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	410286-1
ISSN	1532-8430 ; 0022-0736
ISSN (online)	1532-8430
ISSN	0022-0736
DOI	10.1016/j.jelectrocard.2023.09.011
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Book ; Online: Overparameterized Linear Regression under Adversarial Attacks

Ribeiro, Antônio H. / Schön, Thomas B.

2022

Abstract: We study the error of linear regression in the face of adversarial attacks. In this framework, an adversary changes the input to the regression model in order to maximize the prediction error. We provide bounds on the prediction error in the presence of ... ...

Abstract	We study the error of linear regression in the face of adversarial attacks. In this framework, an adversary changes the input to the regression model in order to maximize the prediction error. We provide bounds on the prediction error in the presence of an adversary as a function of the parameter norm and the error in the absence of such an adversary. We show how these bounds make it possible to study the adversarial error using analysis from non-adversarial setups. The obtained results shed light on the robustness of overparameterized linear models to adversarial attacks. Adding features might be either a source of additional robustness or brittleness. On the one hand, we use asymptotic results to illustrate how double-descent curves can be obtained for the adversarial error. On the other hand, we derive conditions under which the adversarial error can grow to infinity as more features are added, while at the same time, the test error goes to zero. We show this behavior is caused by the fact that the norm of the parameter vector grows with the number of features. It is also established that $\ell_\infty$ and $\ell_2$-adversarial attacks might behave fundamentally differently due to how the $\ell_1$ and $\ell_2$-norms of random projections concentrate. We also show how our reformulation allows for solving adversarial training as a convex optimization problem. This fact is then exploited to establish similarities between adversarial training and parameter-shrinking methods and to study how the training might affect the robustness of the estimated models.
Keywords	Statistics - Machine Learning ; Computer Science - Cryptography and Security ; Computer Science - Machine Learning ; Electrical Engineering and Systems Science - Signal Processing ; Mathematics - Statistics Theory
Subject code	519
Publishing date	2022-04-13
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Potential Epidemic Vulnerability and Socioepidemiological Profile of SARS-CoV2 in the Brazilian Northeast Region.

de Sousa Tavares, Lohanna Valeska / Ribeiro, Antônio Júnior Alves / Christofolini, Denise Maria

Tropical medicine and infectious disease

2023 Volume 8, Issue 4

Abstract: Background: COVID-19 is a significant public health problem that can have a negative impact, especially in vulnerable regions.: Objective: This study aimed to provide evidence that could positively influence coping with COVID-19 based on the ... ...

Abstract	Background: COVID-19 is a significant public health problem that can have a negative impact, especially in vulnerable regions. Objective: This study aimed to provide evidence that could positively influence coping with COVID-19 based on the relationship between the potential epidemic vulnerability index (PEVI) and socioepidemiological variables. This could be used as a decision-making tool for the planning of preventive initiatives in regions with relevant vulnerability indices for the spread of SARS-CoV-2. Methodology: We performed a cross-sectional study, with the analysis of the population characteristics of COVID-19 cases associated with neighborhoods' PEVIs in the conurbation region of Crajubar, northeastern Brazil, through the mapping of socioeconomic-demographic factors and spatial autocorrelation. Results: The PEVI distribution indicated low vulnerability in areas with high real estate and commercial value; as communities moved away from these areas, the vulnerability levels increased. As for the number of cases, three of the five neighborhoods with a high-high autocorrelation, and some other neighborhoods showed a bivariate spatial correlation with a low-low PEVI but also high-low with indicators that make up the PEVI, representing areas that could be protected by public health measures to prevent increases in COVID-19 cases. Conclusions: The impact of the PEVI revealed areas that could be targeted by public policies to decrease the occurrence of COVID-19.
Language	English
Publishing date	2023-03-27
Publishing country	Switzerland
Document type	Journal Article
ISSN	2414-6366
ISSN (online)	2414-6366
DOI	10.3390/tropicalmed8040192
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