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[Language acquisition in CLP children. 3. Results].

Following part I "Fundamentals" and part II "Procedures", this third part presents the findings about language acquisition and the conditions governing this process in 315 CLP children. It has been shown that early language programs for CLP families leads to the linguistic rehabilitation of these children before they reach school age. Semantically and syntactically complex sentences at the age of 2-3 years results in good articulation at age 5-6. Early precision of articulation is usually associated with an increased risk for psychosomatic complications. The complexity of the cleft at birth is of minor importance for language acquisition, whereas early treatment, parents' compliance and avoidance of corrections and sensitizations are decisive for the successful course of the child's language development at the age of 5-6 years.

Child↗
PubMed1996

Sources and effects of low-frequency noise.

The sources of human exposure to low-frequency noise and its effects are reviewed. Low-frequency noise is common as background noise in urban environments, and as an emission from many artificial sources: road vehicles, aircraft, industrial machinery, artillery and mining explosions, and air movement machinery including wind turbines, compressors, and ventilation or air-conditioning units. The effects of low-frequency noise are of particular concern because of its pervasiveness due to numerous sources, efficient propagation, and reduced efficacy of many structures (dwellings, walls, and hearing protection) in attenuating low-frequency noise compared with other noise. Intense low-frequency noise appears to produce clear symptoms including respiratory impairment and aural pain. Although the effects of lower intensities of low-frequency noise are difficult to establish for methodological reasons, evidence suggests that a number of adverse effects of noise in general arise from exposure to low-frequency noise: Loudness judgments and annoyance reactions are sometimes reported to be greater for low-frequency noise than other noises for equal sound-pressure level; annoyance is exacerbated by rattle or vibration induced by low-frequency noise; speech intelligibility may be reduced more by low-frequency noise than other noises except those in the frequency range of speech itself, because of the upward spread of masking. On the other hand, it is also possible that low-frequency noise provides some protection against the effects of simultaneous higher frequency noise on hearing. Research needs and policy decisions, based on what is currently known, are considered.

Auditory Threshold↗
PubMed2005

Toward personal eHealth in cardiology. Results from the EPI-MEDICS telemedicine project.

Despite many attempts to improve the management of acute myocardial infarction, only small trends to shorter time intervals before treatment have been reported. The self-care solution developed by the European EPI-MEDICS project (2001-2004) is a novel, very affordable, easy-to-use, portable, and intelligent Personal ECG Monitor (PEM) for the early detection of cardiac ischemia and arrhythmia that is able to record a professional-quality, 3-lead electrocardiogram (ECG) based on leads I, II, and V2; derive the missing leads of the standard 12-lead ECG (thanks to either a generic or a patient-specific transform), compare each ECG with a reference ECG by means of advanced neural network-based decision-making methods taking into account the serial ECG measurements and the patient risk factors and clinical data; and generate different levels of alarms and forward the alarm messages with the recorded ECGs and the patient's Personal electronic Health Record (PHR) to the relevant health care providers by means of a standard Bluetooth-enabled, GSM/GPRS-compatible mobile phone. The ECG records are SCP-ECG encoded and stored with the PHR on a secure personal SD Card embedded in the PEM device. The alarm messages and the PHR are XML encoded. Major alarm messages are automatically transmitted to the nearest emergency call center. Medium or minor alarms are sent on demand to a central PEM Alarm Web Server. Health professionals are informed by a Short Message Service. The PEM embeds itself a Web server to facilitate the reviewing and/or update of the PHR during a routine visit at the office of the general physician or cardiologist. Eighty PEM prototypes have been finalized and tested for several weeks on 697 citizens/patients in different clinical and self-care situations involving end users (188 patients), general physicians (10), and cardiologists (9). The clinical evaluation indicates that the EPI-MEDICS concept may save lives and is very valuable for prehospitalization triage.

Allied Health Personnel↗
PubMed1993

Automated integration of external databases: a knowledge-based approach to enhancing rule-based expert systems.

Expert system applications in the biomedical domain have long been hampered by the difficulty inherent in maintaining and extending large knowledge bases. We have developed a knowledge-based method for automatically augmenting such knowledge bases. The method consists of automatically integrating data contained in commercially available, external, online databases with data contained in an expert system's knowledge base. We have built a prototype system, named DBX, using this technique to augment an expert system's knowledge base as a decision support aid and as a bibliographic retrieval tool. In this paper, we describe this prototype system in detail, illustrate its use, and discuss the lessons we have learned in its implementation.

Artificial Intelligence↗
PubMed2005

Predicting seizure frequency after epilepsy surgery.

OBJECTIVE: To identify clinical features related to seizure frequency after epilepsy surgery in patients with recurrent seizures. BACKGROUND: No studies have examined the differences between patients who have rare seizures and patients who experience frequent seizures after epilepsy surgery. Since seizure frequency correlates with morbidity and quality of life, it is desirable to know which preoperative clinical features predict postoperative seizure frequency. METHODS: Patients with recurrent seizures were placed in two categories: rare postoperative seizures (< or =2 per year) and frequent postoperative seizures (> or =12 per year) using seizure frequency in the second postoperative year. Variables included preoperative seizure frequency, age of first risk, age at first seizure, epilepsy duration, age at surgery, history of febrile convulsions, tonic-clonic seizures, status epilepticus, or family history, IQ, magnetic resonance imaging (MRI), and positron emission tomography (PET). Variables were analyzed using non-parametric tests to assess relationship to postoperative seizure frequency. RESULTS: Of 475 patients who had epilepsy surgery, 111 had rare or frequent seizures in the second postoperative year. After anterior temporal lobectomy (ATL), age of first risk< or =5 years and presence of mesial temporal sclerosis on MRI were associated with rare seizures (66% of patients), whereas lack of these risk factors was associated with frequent seizures (75% of patients) (p<0.03). For non-ATL operations, preoperative seizure frequency of > or =20 seizures per month was associated with frequent postoperative seizures (p=0.03). No other variables influenced outcome. CONCLUSIONS: Some preoperative clinical features correlate with postoperative seizure frequency in patients with recurrent seizures after epilepsy surgery. This has implications for the surgical decision making process and early postoperative management.

Adolescent↗
PubMed2004

Developmental amnesia: a new pattern of dissociation with intact episodic memory.

A case of developmental amnesia is reported for a child, CL, of normal intelligence, who has intact episodic memory but impaired semantic memory for both semantic knowledge of facts and semantic knowledge of words, including general world knowledge, knowledge of word meanings and superordinate knowledge of words. In contrast to the deficits in semantic memory, there are no impairments in episodic memory for verbal or visual material, assessed by recall or recognition. Lexical decision was also intact, indicating impairment in semantic knowledge of vocabulary rather than absence of lexical representations. The case forms a double dissociation to the cases of Vargha-Khadem et al. [Science 277 (1997) 376; Episodic memory: new directions in research (2002) 153]; Gadian et al. [Brain 123 (2000) 499] for whom semantic memory was intact but episodic memory was impaired. This double dissociation suggests that semantic memory and episodic memory have the capacity to develop separately and supports models of modularity within memory development and a functional architecture for the developmental disorders within which there is residual normality rather than pervasive abnormality. Knowledge of arithmetical facts is also spared for CL, consistent with adult studies arguing for numeracy knowledge distinct from other semantics. Reading was characterised by difficulty with irregular words and homophones but intact reading of nonwords. CL has surface dyslexia with poor lexico-semantic reading skills but good phonological reading skills. The case was identified following screening from a population of normal schoolchildren suggesting that developmental amnesias may be more pervasive than has been recognised previously.

Amnesia↗
PubMed1976

Disaster procedures report. Report following the Moorgate train crash on 28 February, 1975.

There is no substitute for the use of intelligence and common sense both in the drawing up and interpretation of a disaster plan; for compromise in dealing with other rescue services; for ingenuity in filling the gaps in the equipment with which you find yourself provided; and, finally, perhaps most important, for self-discipline. None of us is indispensible--there are always others equally able to make decisions.

Analgesics↗
PubMed2006

Fingerprint recognition using model-based density map.

Utilizing more information other than minutiae is much helpful for large-scale fingerprint recognition applications. In this paper, we proposed a polynomial model to approximate the density map of fingerprints and used the model's parameters as a novel kind of feature for fingerprint representation. Thus, the density information can be utilized into the matching stage with a low additional storage cost. A decision-level fusion scheme is further used to combine the density map matching with conventional minutiae-based matching and experimental results showed a much better performance than using single minutiae-based matching.

Algorithms↗
PubMed2004

Comments on "a parallel mixture of SVMs for very large scale problems".

Collobert, Bengio, and Bengio (2002) recently introduced a novel approach to using a neural network to provide a class prediction from an ensemble of support vector machines (SVMs). This approach has the advantage that the required computation scales well to very large data sets. Experiments on the Forest Cover data set show that this parallel mixture is more accurate than a single SVM, with 90.72% accuracy reported on an independent test set. Although this accuracy is impressive, their article does not consider alternative types of classifiers. We show that a simple ensemble of decision trees results in a higher accuracy, 94.75%, and is computationally efficient. This result is somewhat surprising and illustrates the general value of experimental comparisons using different types of classifiers.

Algorithms↗
PubMed2005

Reliability of old and new ventricular fibrillation detection algorithms for automated external defibrillators.

BACKGROUND: A pivotal component in automated external defibrillators (AEDs) is the detection of ventricular fibrillation by means of appropriate detection algorithms. In scientific literature there exists a wide variety of methods and ideas for handling this task. These algorithms should have a high detection quality, be easily implementable, and work in real time in an AED. Testing of these algorithms should be done by using a large amount of annotated data under equal conditions. METHODS: For our investigation we simulated a continuous analysis by selecting the data in steps of one second without any preselection. We used the complete BIH-MIT arrhythmia database, the CU database, and the files 7001-8210 of the AHA database. All algorithms were tested under equal conditions. RESULTS: For 5 well-known standard and 5 new ventricular fibrillation detection algorithms we calculated the sensitivity, specificity, and the area under their receiver operating characteristic. In addition, two QRS detection algorithms were included. These results are based on approximately 330,000 decisions (per algorithm). CONCLUSION: Our values for sensitivity and specificity differ from earlier investigations since we used no preselection. The best algorithm is a new one, presented here for the first time.

Algorithms↗
PubMed2026

Graph neural network-based risk stratification of prostate cancer using gene expression and SHAP interpretability.

Accurate risk stratification is essential for guiding treatment decisions and preventing over treatment of prostate cancer, which remains one of the most prevalent cancers among adult men. While the Gleason score, obtained from prostate biopsies, is routinely used to assess tumor aggressiveness, the biopsy procedure carries risks such as pain, infection, and, in some cases, serious complications such as sepsis. In this study, we proposed an artificial intelligence-based framework that integrates mRNA expression profiles with functional interaction networks to classify prostate cancer patients into low-, medium-, and high-risk groups defined by Gleason scores. The pipeline comprised five steps: (1) data collection from The Cancer Genome Atlas (TCGA), (2) preprocessing of gene expression data, (3) two-stage feature selection to identify informative biomarkers, (4) risk classification using a dual-branch graph neural network (GNN) that combines gene-gene interaction graphs with sample-level expression features, and (5) model interpretation using SHAP to quantify feature contributions. Differentially expressed genes were identified in the High (ASPN, GMNN, PEBP4, C2, KNCK17), Medium (C2, IGSF1, ASPN, CDKN3, AMH), and Low (TNMD, VWA5B2, ST6GALNAC5, CYP3A5, PHGR1) risk groups, underscoring the molecular heterogeneity of disease progression. On an independent held-out test set, the model achieved AUCs of 0.86, 0.88, and 0.95 for the low-, medium-, and high-risk groups, respectively, with an overall accuracy of 80%. These results suggest that combining GNN-based modeling with explainable AI can capture both global and local molecular patterns relevant to tumor aggressiveness. However, as the model was developed and evaluated solely on the TCGA cohort, the findings should be regarded as exploratory, and external validation will be required to establish generalizability. Within these limitations, the proposed framework highlights the potential of molecular profiling and graph-based deep learning to support more precise, potentially less invasive, risk assessment and individualized treatment planning in prostate cancer.

Prostatic Neoplasms↗
PubMed2001

Drug design by machine learning: support vector machines for pharmaceutical data analysis.

We show that the support vector machine (SVM) classification algorithm, a recent development from the machine learning community, proves its potential for structure-activity relationship analysis. In a benchmark test, the SVM is compared to several machine learning techniques currently used in the field. The classification task involves predicting the inhibition of dihydrofolate reductase by pyrimidines, using data obtained from the UCI machine learning repository. Three artificial neural networks, a radial basis function network, and a C5.0 decision tree are all outperformed by the SVM. The SVM is significantly better than all of these, bar a manually capacity-controlled neural network, which takes considerably longer to train.

Algorithms↗
PubMed2004

[The assessment of (in)competence to make a will].

Based upon German law and jurisdiction, psychiatric literature as well as the author's experiences, essential criteria for the assessment of testamentary capacity are presented, peculiarities of the posthumous assessment of psychopathology are explained and the anachronistic idea of the "lucid interval" is critically discussed. The legal term "freedom to determine one's will", decisive for the competence to contract and to make a will, corresponds to the psychopathological dimension of judgement. In the practice of experts' assessments, this criterion is most likely to be impaired by delusional misinterpretation of reality, lack of insight in being ill, pathological dominance of affects or suggestibility, while cognitive deficits are less often decisive. Using knowledgeably all available sources of information, a posthumous expert's statement on the legal ability to make a will is possible with the reliability legally required in more than 90 % of cases.

Cognition Disorders↗
PubMed2026

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

Humans↗
PubMed2004

An ROC comparison of four methods of combining information from multiple images of the same patient.

Variance of diagnostic information contained in an image degrades diagnostic accuracy. Acquiring multiple images of the same patient (e.g., mediolateral oblique and craniocaudal view mammograms) can, in principle, help reduce this degradation. We demonstrate how this can be accomplished in the context of computer-aided diagnosis (CAD). Assuming that computer outputs obtained from multiple images of the same patient can be transformed monotonically to the same pair of truth-conditional normal distributions and, for simplicity, ignoring correlation among images, we investigate theoretically four methods of combining the computer outputs: taking the average, the median, the maximum, or the minimum. We found, as one would expect, that both the average and the median always produce an improved area under the receiver operating characteristic (ROC) curve (AUC) compared to the single-view images, while the average always produces better performance than the median. However, the maximum and minimum also can produce improved AUCs in some situations, and under certain conditions can outperform the average. Surprisingly, we found that the maximum and minimum of normally-distributed decision variables produce nearly binormal ROC curves. These results can be used as a guide in attempting to increase the efficacy of CAD when multiple images are available from the same patient.

Algorithms↗
PubMed2026

Deep learning-based multimodal pathogenomics integration for precision cancer prognosis.

BACKGROUND: Recent studies have revealed valuable prognostic insights in haematoxylin and eosin (H&E)-stained histological sections and transcriptomic profiles, suggesting potential applications in machine learning. However, existing methods lack sufficient intra- and inter-modal interactions, and face challenges in clinical validation due to incomplete multimodal data. METHODS: We proposed PathoGems (PathoGenomics-based integrative survival prediction), a weakly-supervised, interpretable multimodal learning framework that integrates histology and genomic profiles for precise cancer prognosis prediction. To evaluate the robustness of PathoGems, we initially curated a dataset of 1965 cases across four cohorts from The Cancer Genome Atlas (TCGA), including breast, colorectal, glioblastoma, and esophageal cancers. For external validation, PathoGems was further evaluated on four independent cohorts, consisting of 76 breast cancer and 41 esophageal squamous cell carcinoma cases from Zhejiang Cancer Hospital, as well as 102 colorectal cancer and 58 glioblastoma cases from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). RESULTS: PathoGems effectively stratified patients into favorable and unfavorable risk groups, revealing significant differences in histological patterns, genomic features, and overall survival (log-rank test, p&#x2009;<&#x2009;0.05). Moreover, the model&#x2019;s predictions are further supported by visualization and transcriptomic analysis, enhancing interpretability and reliability. CONCLUSIONS: By fusing histological and clinicogenomic multimodal models, PathoGems will provide a solid foundation for developing an innovative tool that aids clinicians in making informed decisions and selection personalized treatment strategies for cancer patients.

Humans↗
PubMed1992

Out-of-home placement of children with severe handicaps: a comparison of approaches.

The relation of risk factors to out-of-home placement of children with severe and profound mental retardation was examined using both cross-sectional (n = 5,992) and 2-panel (n = 141) designs. Predictor variables included age, sex, ethnicity, adaptive behavior, maladaptive behavior, retardation level, blindness, deafness, and epilepsy. Multivariate analysis of variance indicated significant differences in the relative importance of predictor variables between sampling approaches. However, accuracy in predicting the children placed increased little in the large cross-sectional sample (model accuracy = 72.2%) over the smaller semi-longitudinal one (model accuracy = 70.2%). It appears that factors such as age, adaptive behavior, and maladaptive behavior may be overstated in large, cross-sectional studies of placement, and ethnicity may play a larger role in placement decisions than previous cross-sectional comparisons suggest.

Adolescent↗

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