Related papers: Predicting optimal hematocrit in silico
Modern treatments for Type 1 diabetes (T1D) use devices known as artificial pancreata (APs), which combine an insulin pump with a continuous glucose monitor (CGM) operating in a closed-loop manner to control blood glucose levels. In…
Red blood cells (RBCs) are essential to human health, and their precise morphological analysis is important for diagnosing hematological disorders. Despite the promise of foundation models in medical diagnostics, comprehensive AI solutions…
Identifying predictive features from high-dimensional datasets is a major task in biomedical research. However, it is difficult to determine the robustness of selected features. Here, we investigate the performance of randomly chosen…
Background: Recent studies have used basic epicardial adipose tissue (EAT) assessments (e.g., volume and mean HU) to predict risk of atherosclerosis-related, major adverse cardiovascular events (MACE). Objectives: Create novel, hand-crafted…
An erythrocytes sedimentation rate (ESR) measures how fast a blood sample sediments along a test tube in one hour in a clinical laboratory. Since elevated level of ESR is associated with inflammatory diseases, ESR is one of the routine…
Abdominal computed tomography (CT) scans are frequently performed in clinical settings. Opportunistic CT involves repurposing routine CT images to extract diagnostic information and is an emerging tool for detecting underdiagnosed…
Chronic diseases such as cancer, diabetes, heart diseases, chronic kidney disease (CKD) require a drug management system that ensures a stable and robust output of the patient's condition in response to drug dosage. In the case of CKD, the…
We consider a method for approximate inference in hidden Markov models (HMMs). The method circumvents the need to evaluate conditional densities of observations given the hidden states. It may be considered an instance of Approximate…
Quite generally, constraint-based metabolic flux analysis describes the space of viable flux configurations for a metabolic network as a high-dimensional polytope defined by the linear constraints that enforce the balancing of production…
Using the data on the superconducting critical temperature ($T_{C}$) for a number of metal hydrides, we found a rule that makes it possible to predict the maximum $T_{C}$ based only on the information about the electronic structure of metal…
Objectives: High-grade serous ovarian carcinoma (HGSOC) is typically diagnosed at an advanced stage with extensive peritoneal metastases, making treatment challenging. Neoadjuvant chemotherapy (NACT) is often used to reduce tumor burden…
Purpose: Our objective is to apply an improved statistical global model of beta^- decay half-life systematics [1] generated by machine-learning techniques to the prediction of beta half-lives relevant to r-process nuclei. The primary aim of…
Hypertension is a highly prevalent condition and a major risk factor for cardiovascular disease. The landmark Systolic Blood Pressure Intervention Trial (SPRINT) showed that lowering systolic blood pressure (BP) goals from 140 mmHg to 120…
Leukemia is diagnosed with complete blood counts which is by calculating all blood cells and compare the number of white blood cells (White Blood Cells / WBC) and red blood cells (Red Blood Cells / RBC). Information obtained from a complete…
We have conducted a pilot clinical study to not only investigate the THz spectra of ex-vivo fresh human whole blood of 28 patients following 8-hours fasting guideline, but also to find out the critical blood ingredients of which the…
Recent research on compressed binary hydrides have unveiled the potential for achieving superconductivity at near-room-temperature. Nevertheless, the available decision-making procedures standing behind the selection of constituent elements…
Neutrosophic set has the ability to handle uncertain, incomplete, inconsistent, indeterminate information in a more accurate way. In this paper, we proposed a neutrosophic recommender system to predict the diseases based on neutrosophic set…
Dielectric spectra of human blood reveal a rich variety of dynamic processes. Achieving a better characterization and understanding of these processes not only is of academic interest but also of high relevance for medical applications as,…
This article compares ten recently proposed neural networks and proposes two ensemble neural network-based models for blood glucose prediction. All of them are tested under the same dataset, preprocessing workflow, and tools using the…
Hypertension is a medical condition that is well-established as a risk factor for many major diseases. For example, it can cause alterations in the cardiac structure and function over time that can lead to heart related morbidity and…