The ileum has been candidate more frequently for endoscopic biopsy compared to the past. Most of those biopsies show either completely normal tissue or non-specific changes. Nevertheless, in some diseases, ileal biopsy would be diagnostic, and in some cases, it may be the only anatomical involved location by the disease. Endoscopically, normal mucosal biopsy is unlikely to provide useful diagnostic information and is not routinely recommended. However, in the presence of ileitis, ulcers, or erosions, biopsies can be very helpful. Ileitis might be induced by various conditions including infectious diseases, vasculitis, medication-induced, ischemia, eosinophilic enteritis, tumors etc. The conclusive cause of the condition is proposed by a comprehensive clinical background and physical examination, laboratory investigations, ileocolonoscopy, and imaging findings. Ileoscopy and biopsy are mainly useful in correctly selected cases such as patients who present with inflammatory diarrhea and endoscopic lesions. The purpose of this review article is to provide a simple algorithmic approach to the ileal biopsy samples through several boxes that give diagnostic clues and an idea behind the categories of ileal disorders. This review is written based on those that were previously reported in the literature as well as the authors' experiences. We have summarized different histological patterns in the ileal biopsy specimens that can be used in the diagnosis of inflammatory disorders of the ileum. This review provides an algorithmic approach to the clinicopathological features of inflammatory disorders of the ileum with a brief discussion of some important related issues.
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http://dx.doi.org/10.30699/IJP.2022.539357.2736 | DOI Listing |
JMIR Form Res
January 2025
ICMR-National Institute for Research in Digital Health and Data Science, Ansari Nagar, New Delhi, 110029, India, 91 7840870009.
Background: Verbal autopsy (VA) has been a crucial tool in ascertaining population-level cause of death (COD) estimates, specifically in countries where medical certification of COD is relatively limited. The World Health Organization has released an updated instrument (Verbal Autopsy Instrument 2022) that supports electronic data collection methods along with analytical software for assigning COD. This questionnaire encompasses the primary signs and symptoms associated with prevalent diseases across all age groups.
View Article and Find Full Text PDFEur Heart J Digit Health
January 2025
Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, USA.
Aims: Accurate prediction of clinical outcomes following percutaneous coronary intervention (PCI) is essential for mitigating risk and peri-procedural planning. Traditional risk models have demonstrated a modest predictive value. Machine learning (ML) models offer an alternative risk stratification that may provide improved predictive accuracy.
View Article and Find Full Text PDFEur J Obstet Gynecol Reprod Biol X
March 2025
Mother and Newborn Health Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
This review examines the emerging applications of machine learning (ML) and radiomics in the diagnosis and prediction of placenta accreta spectrum (PAS) disorders, addressing a significant challenge in obstetric care. It highlights recent advancements in ML algorithms and radiomic techniques that utilize medical imaging modalities like magnetic resonance imaging (MRI) and ultrasound for effective classification and risk stratification of PAS. The review discusses the efficacy of various deep learning models, such as nnU-Net and DenseNet-PAS, which have demonstrated superior performance over traditional diagnostic methods through high AUC scores.
View Article and Find Full Text PDFObjectives: The pairing of immunotherapy and radiotherapy in the treatment of locally advanced nonsmall cell lung cancer (NSCLC) has shown promise. By combining radiotherapy with immunotherapy, the synergistic effects of these modalities not only bolster antitumor efficacy but also exacerbate lung injury. Consequently, developing a model capable of accurately predicting radiotherapy- and immunotherapy-related pneumonitis in lung cancer patients is a pressing need.
View Article and Find Full Text PDFInfect Dis Model
June 2025
School of Science, Xi'an University of Technology, Xi'an, 710048, PR China.
During epidemic outbreaks, human behavior is highly influential on the disease transmission and hence affects the course, duration and outcome of the epidemics. In order to examine the feedback effect between the dynamics of the behavioral response and disease outbreak, a simple SIR- type model is established by introducing the independent variable of effective contact rate, characterizing how human behavior interacts with disease transmission dynamics and allowing for the feedback changing over time along the progress of epidemic and population's perception of risk. By a particle swarm optimization algorithm in the solution procedures and time series of COVID-19 data with different shapes of infection peaks, we show that the proposed model, together with such behavioral change mechanism, is capable of capturing the trend of the selected data and can give rise to oscillatory prevalence of different magnitude over time, revealing how different levels of behavioral response affect the waves of infection as well as the evolution of the disease.
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