Quantitative diagnostic algorithm using endocytoscopy for superficial nonampullary duodenal epithelial tumors.

BACKGROUND AND AIM: Optical biopsy using endocytoscopy for superficial nonampullary duodenal epithelial tumors (SNADETs) is practical; however, a diagnostic algorithm has not been established. The aim of this study was to determine correlations of endocytoscopic findings of SNADETs with histology using computer analysis and to establish an algorithm. METHODS: Endocytoscopic images and histological images of duodenal lesions from 70 patients were retrospectively collected. The numbers of glands and densely stained areas with methylene blue (DSMs) per 1 mm2 and the percentage of DSMs per screen in endocytoscopy were determined. Moreover, correlations in DSMs and glands between endocytoscopy and histological images were analyzed. Histopathological diagnoses were assessed according to the revised Vienna classification. The primary outcome was correlation between the number of glands in endocytoscopy and that in histology. Finally, a diagnostic algorithm for endoscopic intervention of SNADETs with a statistical program command was established. RESULTS: The number of glands in endocytoscopic images was correlated with that in histopathological images (ρ 0.64, P < 0.001). There were significant differences in the mean number of glands between category 4/5 and category 3 (P = 0.03) and the mean percentage of DSMs between category 4/5 and category 1 (P < 0.001). When the cutoffs for the number of glands and percentage of DSMs were set at 47 per 1 mm2 and 20.8% in one screen, respectively, the area under the ROC curve was 0.89. CONCLUSIONS: Endocytoscopic images of SNADETs reflect histopathological atypia, and computer analysis provides a practical diagnostic algorithm for endoscopic intervention.

Variation of Chemical Composition and Antioxidant Properties of Kiwiberry (Actinidia arguta) in a Three-Year Study.

The quality of fruit as a source of bioactive ingredients is related to the genetic characteristics of plants, but it can also be modified by growing conditions. Therefore, long-term research can be extremely valuable in evaluating various crop plants, especially novel ones. The aim of the research was to test four popular European kiwiberry (Actinidia arguta) cultivars ('Geneva', 'Bingo', 'Weiki', 'Anna') in terms of selected morphological features, yield, and chemical composition as well as their variability over 3 years. It can be concluded that the studied genotypes were very diverse in terms of the biochemical compounds' concentration in individual seasons. The cultivars 'Anna' and 'Weiki' were the most similar ones with respect to each other in terms of morphology and chemical composition. The cultivars 'Bingo' and 'Geneva' were definitely different. 'Bingo' was characterized by the largest and most uniform fruits in each season and had the highest concentration of vitamin C but the lowest carotenoid concentration. In turn, 'Geneva' produced the smallest fruit in each season with the highest concentration of polyphenols and a high concentration of carotenoids and displayed the highest antioxidant capacity regardless of the determination method. The research was performed with the application of computer-supported statistical analysis.

Long-Term Continuous Computer Registration and Analysis of Motor Activity of a Group of Zebrafish Danio rerio.

A new algorithm for long-term continuous computer recording and analysis of motor activity of a group of zebrafish in the home tank has been developed. The movements of a group of Danio rerio during the entire light period and for several days are recorded at a frequency of 1 frame/sec in the form of short (15 min) files. Then these files are analyzed by the unique DanioStudo software, which, using a threshold algorithm and appropriate masks, calculates for each frame the sum of pixels associated with fish (the sum of fish silhouettes), and for two consecutive frames, the sum of altered pixels (the sum of altered fish silhouettes). The following indexes are calculated: the rate of sum of silhouettes alteration as the ratio of the sum of altered silhouettes to the sum of silhouettes (1) and the time spent in the selected area of the home tank as the ratio of the sum of silhouettes in this area to the sum of silhouettes in the entire tank (2). The mean rate of silhouette alteration correlates to the length of the path travelled by the fish and, therefore, serves as a correct measure of the motor activity of a group of fish. Using these algorithms, completely new data were obtained: it was shown that the motor activity of fish remains constant throughout the entire light period, but depends on the size of the home tank. The proposed approach, together with the DanioStudio software, can be effective in studying the dynamics of changes in the behavior of fish under long-term exposure to short daylight, drugs and toxic substances.

A Survey of Methods and Technologies Used for Diagnosis of Scoliosis.

The purpose of this article is to present diagnostic methods used in the diagnosis of scoliosis in the form of a brief review. This article aims to point out the advantages of select methods. This article focuses on general issues without elaborating on problems strictly related to physiotherapy and treatment methods, which may be the subject of further discussions. By outlining and categorizing each method, we summarize relevant publications that may not only help introduce other researchers to the field but also be a valuable source for studying existing methods, developing new ones or choosing evaluation strategies.

Neural Reduction of Image Data in Order to Determine the Quality of Malting Barley.

Image analysis using neural modeling is one of the most dynamically developing methods employing artificial intelligence. The feature that caused such widespread use of this technique is mostly the ability of automatic generalization of scientific knowledge as well as the possibility of parallel analysis of the empirical data. A properly conducted learning process of artificial neural network (ANN) allows the classification of new, unknown data, which helps to increase the efficiency of the generated models in practice. Neural image analysis is a method that allows extracting information carried in the form of digital images. The paper focuses on the determination of imperfections such as contaminations and damages in the malting barley grains on the basis of information encoded in the graphic form represented by the digital photographs of kernels. This choice was dictated by the current state of knowledge regarding the classification of contamination that uses undesirable features of kernels to exclude them from use in the malting industry. Currently, a qualitative assessment of kernels is carried by malthouse-certified employees acting as experts. Contaminants are separated from a sample of malting barley manually, and the percentages of previously defined groups of contaminations are calculated. The analysis of the problem indicates a lack of effective methods of identifying the quality of barley kernels, such as the use of information technology. There are new possibilities of using modern methods of artificial intelligence (such as neural image analysis) for the determination of impurities in malting barley. However, there is the problem of effective compression of graphic data to a form acceptable for ANN simulators. The aim of the work is to develop an effective procedure of graphical data compression supporting the qualitative assessment of malting barley with the use of modern information technologies. Image analysis can be implemented into dedicated software.

[Influence of morphological parameters of natural teeth and fixed partial dentures supported by dental implants on the time of occlusion]. / Vliyanie morfologicheskikh parametrov estestvennykh zubov i nes"emnykh ortopedicheskikh konstruktsii s oporoi na dental'nye implantaty na vremya okklyuzii.

OBJECTIVE: To study the effect of morphological parameters of natural teeth and fixed partial dentures supported by dental implants on the time of occlusion. MATERIAL AND METHODS: The study of the morphological parameters of the first right upper and lower molars of natural teeth and fixed partial dentures supported by dental implants in the positions of the first molars of the upper and lower jaws, followed by determination of the relationship between the obtained data and the occlusion time using mathematical and statistical analysis. RESULTS: The study of the morphology of the occlusal surface of natural teeth and fixed partial dentures supported by dental implants did not reveal significant differences in the results of measuring the distances between the cusps of the upper and lower first molars, both natural teeth and fixed partial dentures supported by dental implants. However, the angles of the slopes of the cusps and the angles between cusps in natural teeth are sharper than those of artificial crowns. CONCLUSION: According to the correlation analysis in both groups, the relationship between the occlusion time and the morphological parameters of the lower molars was determined; the relationship between the morphological parameters of the upper molars and the occlusion time was not revealed.

[Pilot surveillance and evaluation of influenza-like illness based on automatic computer analysis of electronic medical record in sentinel hospital].

Objective: To compare the accuracy of influenza-like illness (ILI) surveillance by automatic computer analysis based on electronic medical records and by doctor's report. Methods: A total of 3 542 patients who presented to Yichang Central Hospital fever clinic, respiratory department or emergency department between April to October 2019 with an ICD-10 code for acute respiratory illness (J00-J22) and complete electronic medical information of ILI related syndromes were drawn as the study sample. Taking the classification of the study sample according to the ILI case definition by influenza surveillance professionals as the gold standard, draw the receiver operating characteristic (ROC) curve and calculate sensitivity, specificity, diagnostic consistency to compared the accuracy of ILI surveillance by automatic computer analysis and by doctor's report. Results: Median age of 3 542 cases was 30 (24, 38) years old; 1 179 cases (33.29%) compliance with the case definition, ILI reported by doctors was 1 306 cases (36.87%), and computer automatic identification ILI were 1 150 cases (32.47%); 1 391 (39.27%) cases were men. The results of automatic computer analysis and doctor report consistency of kappa values with gold standard judgment were 0.97 and 0.66 respectively; area under the ROC curve was 0.98 and 0.84, respectively. And the sensitivity and specificity of automatic computer analysis were higher than that of doctor's report (all P values were <0.001), the sensitivity was 96.95% and 82.27%, and the specificity was 99.70% and 85.78%, respectively. Conclusion: The automatic computer analysis based on electronic medical records can identified ILI cases with good sensitivity and specificity in ILI case surveillance.

Synergistic application of pulmonary 18F-FDG PET/HRCT and computer-based CT analysis with conventional severity measures to refine current risk stratification in idiopathic pulmonary fibrosis (IPF).

INTRODUCTION: To investigate the combined performance of quantitative CT (qCT) following a computer algorithm analysis (IMBIO) and 18F-FDG PET/CT to assess survival in patients with idiopathic pulmonary fibrosis (IPF). METHODS: A total of 113 IPF patients (age 70 ± 9 years) prospectively and consecutively underwent 18F-FDG PET/CT and high-resolution CT (HRCT) at our institution. During a mean follow-up of 29.6 ± 26 months, 44 (48%) patients died. As part of the qCT analysis, pattern evaluation of HRCT (using IMBIO software) included the total extent (percentage) of the following features: normal-appearing lung, hyperlucent lung, parenchymal damage (comprising ground-glass opacification, reticular pattern and honeycombing), and the pulmonary vessels. The maximum (SUVmax) and minimum (SUVmin) standardized uptake value (SUV) for 18F-FDG uptake in the lungs, and the target-to-background (SUVmax/SUVmin) ratio (TBR) were quantified using routine region-of-interest (ROI) analysis. Pulmonary functional tests (PFTs) were acquired within 14 days of the PET/CT/HRCT scan. Kaplan-Meier (KM) survival analysis was used to identify associations with mortality. RESULTS: Data from 91 patients were available for comparative analysis. The average ± SD GAP [gender, age, physiology] score was 4.2 ± 1.7 (range 0-8). The average ± SD SUVmax, SUVmin, and TBR were 3.4 ± 1.4, 0.7 ± 0.2, and 5.6 ± 2.8, respectively. In all patients, qCT analysis demonstrated a predominantly reticular lung pattern (14.9 ± 12.4%). KM analysis showed that TBR (p = 0.018) and parenchymal damage assessed by qCT (p = 0.0002) were the best predictors of survival. Adding TBR and qCT to the GAP score significantly increased the ability to differentiate between high and low risk (p < 0.0001). CONCLUSION: 18F-FDG PET and qCT are independent and synergistic in predicting mortality in patients with IPF.

[Peculiarities of the functional state of the brain in long-livers and their relatives.]

This paper presents findings of the comparative computer analysis of brain bioelectrical activity (EEG) in three groups of rural population, which include: long-livers, their close relatives, and representatives of families without records of longevity (the latter was conventionally accepted as the «control group¼). Registration of EEG was carried out in conditions of quiet wakefulness with eyes closed. For each group, the average spectral power, frequency characteristics, EEG indices in the ranges of δ-, θ-, α- and ß-rhythms were estimated. The results have revealed the increased ascending effects of the synchronizing link and the weakening of the activating assumptions of non-specific brain systems in long-livers, which we consider as reflection of inhibitory mechanisms which are required to replenish the mobilization resources. With regard to the group of relatives, there were revealed a smaller percentage of δ-rhythm and a greater severity of the α-rhythm index in the temporal areas, as compared to the control group, which is indicative of a more optimal level of processes responsible for memory, integration of afferent (auditory and visual) information and harmonization of the emotional background.

Fetal heart rate short term variation during labor in relation to scalp blood lactate concentration.

INTRODUCTION: Fetal heart rate short term variation (STV) decreases with severe chronic hypoxia in the antenatal period. However, only limited research has been done on STV during labor. We have tested a novel algorithm for a valid baseline estimation and calculated STV. To explore the value of STV during labor, we compared STV with fetal scalp blood (FBS) lactate concentration, an early marker in the hypoxic process. MATERIAL AND METHODS: Software was developed which estimates baseline frequency using a novel algorithm and thereby calculates STV according to Dawes and Redman in up to four 30-minute blocks prior to each FBS. Cardiotocography traces from 1070 women in labor who had had FBS performed on 2134 occasions were analyzed. RESULTS: In acidemic cases (lactate >4.8 mmol/L; Lactate Pro™), median STV 30 minutes prior to FBS was 7.10 milliseconds compared with 6.09 milliseconds in the preacidemic (4.2-4.8 mmol/L) and 5.23 milliseconds in the normal (<4.2 mmol/L) groups (P < .05). There was a positive correlation between lactate and STV (rho = 0.16-0.24; P < .05). Median lactate concentration in cases with STV <3.0 milliseconds (n = 160) was 2.3 mmol/L. When 2 FBS were performed within 60 minutes the change rate of lactate correlated to STV (rho = 0.33; P < .001). Cases with increasing lactate concentration had a median STV of 5.29 milliseconds vs 4.41 milliseconds in those with decreasing lactate (P < .001). CONCLUSIONS: In the early stages of intrapartum hypoxia, STV increases, contrary to findings regarding chronic hypoxia in the antenatal period. The increase in the adrenergic surge is a likely explanation.

Evaluation of visual and computer-based CT analysis for the identification of functional patterns of obstruction and restriction in hypersensitivity pneumonitis.

BACKGROUND AND OBJECTIVE: To determine whether computer-based quantification (CALIPER software) is superior to visual computed tomography (CT) scoring in the identification of CT patterns indicative of restrictive and obstructive functional indices in hypersensitivity pneumonitis (HP). METHODS: A total of 135 consecutive HP patients had CT parenchymal patterns evaluated quantitatively by both visual scoring and CALIPER. Results were evaluated against: forced vital capacity (FVC), total lung capacity (TLC), diffusing capacity for carbon monoxide (DLCO ) and a composite physiological index (CPI) to identify which CT scoring method better correlated with functional indices. RESULTS: CALIPER-derived scores of total interstitial lung disease extent correlated more strongly than visual scores: FVC (CALIPER R = 0.73, visual R = 0.51); DLCO (CALIPER R = 0.61, visual R = 0.48); and CPI (CALIPER R = 0·70, visual R = 0·55). The CT variable that correlated most strongly with restrictive functional indices was CALIPER pulmonary vessel volume (PVV): FVC R = 0.75, DLCO R = 0.68 and CPI R = 0.76. Ground-glass opacity quantified by CALIPER alone demonstrated strong associations with restrictive functional indices: CALIPER FVC R = 0.65; DLCO R = 0.59; CPI R = 0.64; and visual = not significant. Decreased attenuation lung quantified by CALIPER was a better morphological measure of obstructive lung disease than equivalent visual scores as judged by relationships with TLC (CALIPER R = 0.63 and visual R = 0.12). All results were maintained on multivariate analysis. CONCLUSION: CALIPER improved on visual scoring in HP as judged by restrictive and obstructive functional correlations. Decreased attenuation regions of the lung quantified by CALIPER demonstrated better linkages to obstructive lung physiology than visually quantified CT scores. A novel CALIPER variable, the PVV, demonstrated the strongest linkages with restrictive functional indices and could represent a new automated index of disease severity in HP.

Automatic Estimation of Volumetric Breast Density Using Artificial Neural Network-Based Calibration of Full-Field Digital Mammography: Feasibility on Japanese Women With and Without Breast Cancer.

Breast cancer is the most common invasive cancer among women and its incidence is increasing. Risk assessment is valuable and recent methods are incorporating novel biomarkers such as mammographic density. Artificial neural networks (ANN) are adaptive algorithms capable of performing pattern-to-pattern learning and are well suited for medical applications. They are potentially useful for calibrating full-field digital mammography (FFDM) for quantitative analysis. This study uses ANN modeling to estimate volumetric breast density (VBD) from FFDM on Japanese women with and without breast cancer. ANN calibration of VBD was performed using phantom data for one FFDM system. Mammograms of 46 Japanese women diagnosed with invasive carcinoma and 53 with negative findings were analyzed using ANN models learned. ANN-estimated VBD was validated against phantom data, compared intra-patient, with qualitative composition scoring, with MRI VBD, and inter-patient with classical risk factors of breast cancer as well as cancer status. Phantom validations reached an R 2 of 0.993. Intra-patient validations ranged from R 2 of 0.789 with VBD to 0.908 with breast volume. ANN VBD agreed well with BI-RADS scoring and MRI VBD with R 2 ranging from 0.665 with VBD to 0.852 with breast volume. VBD was significantly higher in women with cancer. Associations with age, BMI, menopause, and cancer status previously reported were also confirmed. ANN modeling appears to produce reasonable measures of mammographic density validated with phantoms, with existing measures of breast density, and with classical biomarkers of breast cancer. FFDM VBD is significantly higher in Japanese women with cancer.

Longitudinal evaluation of computerized cardiotocographic parameters throughout pregnancy in normal fetuses: a prospective cohort study.

INTRODUCTION: The longitudinal cardiotocographic (CTG) changes throughout pregnancy in normal fetuses have never been fully described. We aimed at characterizing the evolution of CTG parameters in healthy fetuses, from 24 to 41 weeks of gestation. MATERIAL AND METHODS: A prospective cohort study was conducted in singleton fetuses without structural abnormalities on second-trimester ultrasound. At least one CTG was performed in each of the following intervals: 24-26 weeks(+6d) , 27-29 weeks(+6d) , 30-32 weeks(+6d) , 33-35 weeks(+6d) , 36-38 weeks(+6d) and ≥39 weeks; tracings were analyzed by the OMNIVIEW-SISPORTO 3.6 system. Cases of preterm delivery, fetal death, birthweight under the 10th percentile, low five-minute Apgar, umbilical artery acidemia or neonatal intensive care unit admission were subsequently excluded. RESULTS: A total of 1049 eligible tracings were obtained from 145 fetuses. There was a significant increase over time in average long-term variability (LTV), average short-term variability (STV), number of accelerations and uterine contractions. Conversely, fetal heart rate (FHR) baseline and number of decelerations decreased. A high inter-fetal variability was observed, but there was considerable intra-fetal consistency. Fetuses showing a marked decrease in FHR baseline and those with a marked increase in average LTV had a significantly lower birthweight. Cesarean section rate was significantly higher in cases with a decrease in average STV throughout gestation. CONCLUSIONS: This prospective longitudinal study shows an evolution in computerized CTG parameters during pregnancy, indicating the need to adapt interpretation criteria based on gestational age. The high inter-fetal variability and considerable intra-fetal consistency suggests the possible value of using each fetus as its own reference in serial assessments.

Computer-aided auscultation of murmurs in children: evaluation of commercially available software.

BACKGROUND: Heart murmurs are common in children and may represent congenital or acquired cardiac pathology. Auscultation is challenging and many primary-care physicians lack the skill to differentiate innocent from pathologic murmurs. We sought to determine whether computer-aided auscultation (CardioscanTM) identifies which children require referral to a cardiologist. METHODS: We consecutively enrolled children aged between 0 and 17 years with a murmur, innocent or pathologic, being evaluated in a tertiary-care cardiology clinic. Children being evaluated for the first time and patients with known cardiac pathology were eligible. We excluded children who had undergone cardiac surgery previously or were unable to sit still for auscultation. CardioscanTM auscultation was performed in a quiet room with the subject in the supine position. The sensitivity and specificity of a potentially pathologic murmur designation by CardioscanTM - that is, requiring referral - was determined using echocardiography as the reference standard. RESULTS: We enrolled 126 subjects (44% female) with a median age of 1.7 years, with 93 (74%) having cardiac pathology. The sensitivity and specificity of a potentially pathologic murmur determination by CardioscanTM for identification of cardiac pathology were 83.9 and 30.3%, respectively, versus 75.0 and 71.4%, respectively, when limited to subjects with a heart rate of 50-120 beats per minute. The combination of a CardioscanTM potentially pathologic murmur designation or an abnormal electrocardiogram improved sensitivity to 93.5%, with no haemodynamically significant lesions missed. CONCLUSIONS: Sensitivity of CardioscanTM when interpreted in conjunction with an abnormal electrocardiogram was high, although specificity was poor. Re-evaluation of computer-aided auscultation will remain necessary as advances in this technology become available.

Promises and pitfalls of machine scoring of the Index of Productive Syntax.

The AC-IPSyn computerised system for scoring the Index of Productive Syntax (IPSyn) was evaluated. Twenty language samples, ten taken at 30 months and ten of the same children at 42 months, were each scored for the IPSyn by hand and by AC-IPSyn. Point differences and point-to-point reliability were examined at the levels of the total, subscale, and individual structure scores. Points missed and erroneously given at each level were also analysed. The difference in total scores between manual and AC-IPSyn scoring was relatively small; point-to-point agreement was lower than reported elsewhere. Age differences were also found. AC-IPSyn accuracy varied by subscale and structure, with results suggesting that AC-IPSyn be used at this point in conjunction with hand scoring of more error-prone and low frequency structures. The relatively small total point difference masked the lower reliability revealed by other measures, demonstrating the importance of detailed comparisons of manual and machine scoring.

Toward Understanding the Size Dependence of Shape Features for Predicting Spiculation in Lung Nodules for Computer-Aided Diagnosis.

We analyze the importance of shape features for predicting spiculation ratings assigned by radiologists to lung nodules in computed tomography (CT) scans. Using the Lung Image Database Consortium (LIDC) data and classification models based on decision trees, we demonstrate that the importance of several shape features increases disproportionately relative to other image features with increasing size of the nodule. Our shaped-based classification results show an area under the receiver operating characteristic (ROC) curve of 0.65 when classifying spiculation for small nodules and an area of 0.91 for large nodules, resulting in a 26% difference in classification performance using shape features. An analysis of the results illustrates that this change in performance is driven by features that measure boundary complexity, which perform well for large nodules but perform relatively poorly and do no better than other features for small nodules. For large nodules, the roughness of the segmented boundary maps well to the semantic concept of spiculation. For small nodules, measuring directly the complexity of hard segmentations does not yield good results for predicting spiculation due to limits imposed by spatial resolution and the uncertainty in boundary location. Therefore, a wider range of features, including shape, texture, and intensity features, are needed to predict spiculation ratings for small nodules. A further implication is that the efficacy of shape features for a particular classifier used to create computer-aided diagnosis systems depends on the distribution of nodule sizes in the training and testing sets, which may not be consistent across different research studies.

Three-Dimensional Morphometric Analysis of the Volar Cortical Shape of the Lunate Facet of the Distal Radius.

In cases of distal radius fractures, the fixation of the volar lunate facet fragment is crucial for preventing volar subluxation of the carpal bones. This study aims to clarify the sex differences in the volar morphology of the lunate facet of the distal radius and its relationship with the transverse diameter of the distal radius. Sixty-four CT scans of healthy wrists (30 males and 34 females) were evaluated. Three-dimensional (3D) images of the distal radius were reconstructed from the CT data. We defined reference point 1 as the starting point of the inclination toward the distal volar edge, reference point 2 as the volar edge of the joint on the bone axis, and reference point 3 as the volar edge of the distal radius lunate facet. From the 3D coordinates of reference points 1 to 3, the bone axis distance, volar-dorsal distance, radial-ulnar distance, 3D straight-line distance, and inclination angle were measured. The transverse diameter of the radius was measured, and its correlations with the parameters were evaluated. It was found that in males, compared to females, the transverse diameter of the radius is larger and the protrusion of the volar lunate facet is greater. This suggests that the inclination of the volar surface is steeper in males and that the volar locking plate may not fit properly with the volar cortical bone of the lunate facet, necessitating additional fixation.

Evaluation of the repeatability of kinesiological measurements of spontaneous infant movements using OSESEC computer analysis algorithms.

Purpose: There is a need to create objective and reproducible tool for assessing the quality of infant movements. It's substantially important to detect movement disorders in infants as early as possible. The study aimed to evaluate the reproducibility of kinesiological measurements of spontaneous movements performed by 51 infants (aged 6 to 15 weeks) recorded three times for two consecutive days using OSESEC computer analysis algorithms by determining numerical values of parameters, i.e., speed, acceleration, direction, and movement trajectory. Methods: The study group consisted of 51 infants. The diagnostic method of Prechtl was used for qualitative assessment. The quantitative assessment was based on the use of a OSESEC system. Numerical values for all movement parameters were determined, and the data obtained in the study were used for statistical analysis. Results: Analysis including movement parameter values on three consecutive recordings for the same infant revealed no statistically significant differences in location ( p = 0.073), range ( p = 0.557), shape ( p = 0.289), mean acceleration ( p = 0.124) and mean speed ( p = 0.767). This confirms the reproducibility of measurements of the proposed parameters of the objectification of spontaneous infant movements. Conclusions: The interpretability and accuracy of the presented parameters were proved. All parameters estimation is fully automated. Further research and testing requires a larger study group to create an objective diagnostic device for infants.

Artificial intelligence (AI)-assisted chest computer tomography (CT) insights: a study on intensive care unit (ICU) admittance trends in 78 coronavirus disease 2019 (COVID-19) patients.

Background: The global coronavirus disease 2019 (COVID-19) pandemic has posed substantial challenges for healthcare systems, notably the increased demand for chest computed tomography (CT) scans, which lack automated analysis. Our study addresses this by utilizing artificial intelligence-supported automated computer analysis to investigate lung involvement distribution and extent in COVID-19 patients. Additionally, we explore the association between lung involvement and intensive care unit (ICU) admission, while also comparing computer analysis performance with expert radiologists' assessments. Methods: A total of 81 patients from an open-source COVID database with confirmed COVID-19 infection were included in the study. Three patients were excluded. Lung involvement was assessed in 78 patients using CT scans, and the extent of infiltration and collapse was quantified across various lung lobes and regions. The associations between lung involvement and ICU admission were analysed. Additionally, the computer analysis of COVID-19 involvement was compared against a human rating provided by radiological experts. Results: The results showed a higher degree of infiltration and collapse in the lower lobes compared to the upper lobes (P<0.05). No significant difference was detected in the COVID-19-related involvement of the left and right lower lobes. The right middle lobe demonstrated lower involvement compared to the right lower lobes (P<0.05). When examining the regions, significantly more COVID-19 involvement was found when comparing the posterior vs. the anterior halves and the lower vs. the upper half of the lungs. Patients, who required ICU admission during their treatment exhibited significantly higher COVID-19 involvement in their lung parenchyma according to computer analysis, compared to patients who remained in general wards. Patients with more than 40% COVID-19 involvement were almost exclusively treated in intensive care. A high correlation was observed between computer detection of COVID-19 affections and the rating by radiological experts. Conclusions: The findings suggest that the extent of lung involvement, particularly in the lower lobes, dorsal lungs, and lower half of the lungs, may be associated with the need for ICU admission in patients with COVID-19. Computer analysis showed a high correlation with expert rating, highlighting its potential utility in clinical settings for assessing lung involvement. This information may help guide clinical decision-making and resource allocation during ongoing or future pandemics. Further studies with larger sample sizes are warranted to validate these findings.

Comparison of fetal heart rate baseline estimation by the cardiotocograph network and clinicians: a multidatabase retrospective assessment study.

Background: This study aims to compare the fetal heart rate (FHR) baseline predicted by the cardiotocograph network (CTGNet) with that estimated by clinicians. Material and methods: A total of 1,267 FHR recordings acquired with different electrical fetal monitors (EFM) were collected from five datasets: 84 FHR recordings acquired with F15 EFM (Edan, Shenzhen, China) from the Guangzhou Women and Children's Medical Center, 331 FHR recordings acquired with SRF618B5 EFM (Sanrui, Guangzhou, China), 234 FHR recordings acquired with F3 EFM (Lian-Med, Guangzhou, China) from the NanFang Hospital of Southen Medical University, 552 cardiotocographys (CTG) recorded using STAN S21 and S31 (Neoventa Medical, Mölndal, Sweden) and Avalon FM40 and FM50 (Philips Healthcare, Amsterdam, The Netherlands) from the University Hospital in Brno, Czech Republic, and 66 FHR recordings acquired using Avalon FM50 fetal monitor (Philips Healthcare, Amsterdam, The Netherlands) at St Vincent de Paul Hospital (Lille, France). Each FHR baseline was estimated by clinicians and CTGNet, respectively. And agreement between CTGNet and clinicians was evaluated using the kappa statistics, intra-class correlation coefficient, and the limits of agreement. Results: The number of differences <3 beats per minute (bpm), 3-5 bpm, 5-10 bpm and ≥10 bpm, is 64.88%, 15.94%, 14.44% and 4.74%, respectively. Kappa statistics and intra-class correlation coefficient are 0.873 and 0.969, respectively. Limits of agreement are -6.81 and 7.48 (mean difference: 0.36 and standard deviation: 3.64). Conclusion: An excellent agreement was found between CTGNet and clinicians in the baseline estimation from FHR recordings with different signal loss rates.