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Mashup Score: 94
Background A blockchain can be described as a distributed ledger database where, under a consensus mechanism, data are permanently stored in records, called blocks, linked together with cryptography. Each block contains a cryptographic hash function of the previous block, a timestamp, and transaction data, which are permanently stored in thousands of nodes and never altered. This provides a potential real-world application for generating a permanent, decentralized record of scientific data, taking advantage of blockchain features such as timestamping and immutability. Implementation Here, we propose INNBC DApp, a Web3 decentralized application providing a simple front-end user interface connected with a smart contract for recording scientific data on a modern, proof-of-stake (POS) blockchain such as BNB Smart Chain. Unlike previously proposed blockchain tools that only store a hash of the data on-chain, here the data are stored fully on-chain within the transaction itself as “transacti
Categories: General Medicine News, General HCPsTweet
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Mashup Score: 6
Background Atrial fibrillation (AF) is a major risk factor for ischemic stroke, and early AF diagnosis may reduce associated morbidity and mortality. A 10-variable predictive model (UNAFIED) was previously developed to estimate patients’ 2-year AF risk. This study evaluated a clinical workflow incorporating UNAFIED for screening, education, and follow-up evaluation of patients visiting a cardiology clinic who may be at an elevated risk of developing AF within 2 years. Methods Patients were included if they were aged ≥ 40 years with a scheduled in-person visit at the Eskenazi Health Cardiology Clinic between October 25, 2021, and August 10, 2022. Clinical decision support identified patients with an elevated AF risk. Initial screening with 1-lead electrocardiogram devices was offered, and routine clinical practice for diagnosis and management was followed. Physicians were surveyed on their use of the workflow, attitudes toward implementation, and perceived impact on patient care. Result
Categories: General Medicine News, CardiologistsTweet-
Screening for undiagnosed atrial fibrillation using an electronic health record‒based clinical prediction model: clinical pilot implementation initiative | EHR+AI+Kardia = clinically valuable screening for #Afib. https://t.co/AaNVku2n1P
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Mashup Score: 98
Background A blockchain can be described as a distributed ledger database where, under a consensus mechanism, data are permanently stored in records, called blocks, linked together with cryptography. Each block contains a cryptographic hash function of the previous block, a timestamp, and transaction data, which are permanently stored in thousands of nodes and never altered. This provides a potential real-world application for generating a permanent, decentralized record of scientific data, taking advantage of blockchain features such as timestamping and immutability. Implementation Here, we propose INNBC DApp, a Web3 decentralized application providing a simple front-end user interface connected with a smart contract for recording scientific data on a modern, proof-of-stake (POS) blockchain such as BNB Smart Chain. Unlike previously proposed blockchain tools that only store a hash of the data on-chain, here the data are stored fully on-chain within the transaction itself as “transacti
Categories: General Medicine News, General HCPsTweet-
An article published in #BMCMedInformDecisMak presents INNBC DApp: a decentralized application providing a simple front-end user interface connected with a smart contract for recording scientific data on a modern, proof-of-stake blockchain. https://t.co/q6BmOQAVIw
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Mashup Score: 3
Introduction Remote monitoring can strengthen postoperative care in the community and minimise the burden of complications. However, implementation requires a clear understanding of how to sustainably integrate such complex interventions into existing care pathways. This study aimed to explore perceptions of potential facilitators and barriers to the implementation of digital remote postoperative monitoring from key stakeholders and derive recommendations for an implementable service. Methods A qualitative implementation study was conducted of digital remote postoperative wound monitoring across two UK tertiary care hospitals. All enrolled patients undergoing general surgery, and all staff involved in postoperative care were eligible. Criterion-based purposeful sampling was used to select stakeholders for semi-structured interviews on their perspectives and experiences of digital remote postoperative monitoring. A theory-informed deductive-inductive qualitative analysis was conducted;
Categories: General Medicine News, General HCPsTweet-
Implementation of digital remote postoperative monitoring in routine practice: a qualitative study of barriers and facilitators #some4surgery https://t.co/l7yPuUCmMX
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Mashup Score: 12A time series algorithm to predict surgery in neonatal necrotizing enterocolitis - BMC Medical Informatics and Decision Making - 3 month(s) ago
Background Determining the optimal timing of surgical intervention for Neonatal necrotizing enterocolitis (NEC) poses significant challenges. This study develops a predictive model using the long short-term memory network (LSTM) with a focal loss (FL) to identify infants at risk of developing Bell IIB + NEC early and issue timely surgical warnings. Methods Data from 791 neonates diagnosed with NEC are gathered from the Neonatal Intensive Care Unit (NICU), encompassing 35 selected features. Infants are categorized into those requiring surgical intervention (n = 257) and those managed medically (n = 534) based on the Mod-Bell criteria. A fivefold cross-validation approach is employed for training and testing. The LSTM algorithm is utilized to capture and utilize temporal relationships in the dataset, with FL employed as a loss function to address class imbalance. Model performance metrics include precision, recall, F1 score, and average precision (AP). Results The model tested on a real
Categories: General Medicine News, General HCPsTweet-
A time series algorithm to predict surgery in neonatal necrotizing enterocolitis #some4pedsurg #some4surgery #BMC Medical Informatics and Decision Making https://t.co/sIUntJznIB
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Mashup Score: 2Predicting high blood pressure using machine learning models in low- and middle-income countries - BMC Medical Informatics and Decision Making - 3 month(s) ago
Responding to the rising global prevalence of noncommunicable diseases (NCDs) requires improvements in the management of high blood pressure. Therefore, this study aims to develop an explainable machine learning model for predicting high blood pressure, a key NCD risk factor, using data from the STEPwise approach to NCD risk factor surveillance (STEPS) surveys. Nationally representative samples of adults aged 18-69 years were acquired from 57 countries spanning six World Health Organization (WHO) regions. Data harmonization and processing were performed to standardize the selected predictors and synchronize features across countries, yielding 41 variables, including demographic, behavioural, physical, and biochemical factors. Five machine learning models – logistic regression, k-nearest neighbours, random forest, XGBoost, and a fully connected neural network – were trained and evaluated at global, regional, and country-specific levels using an 80/20 train-test split. The models’ perfor
Categories: General Medicine News, General HCPsTweet-
A study published in #BMCMedInformDecisMak demonstrates the potential of applying machine learning techniques to large-scale health datasets for predicting blood pressure status in low-and middle-income countries. https://t.co/ox7lgEQCUU
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Mashup Score: 2Predicting high blood pressure using machine learning models in low- and middle-income countries - BMC Medical Informatics and Decision Making - 3 month(s) ago
Responding to the rising global prevalence of noncommunicable diseases (NCDs) requires improvements in the management of high blood pressure. Therefore, this study aims to develop an explainable machine learning model for predicting high blood pressure, a key NCD risk factor, using data from the STEPwise approach to NCD risk factor surveillance (STEPS) surveys. Nationally representative samples of adults aged 18-69 years were acquired from 57 countries spanning six World Health Organization (WHO) regions. Data harmonization and processing were performed to standardize the selected predictors and synchronize features across countries, yielding 41 variables, including demographic, behavioural, physical, and biochemical factors. Five machine learning models – logistic regression, k-nearest neighbours, random forest, XGBoost, and a fully connected neural network – were trained and evaluated at global, regional, and country-specific levels using an 80/20 train-test split. The models’ perfor
Categories: General Medicine News, General HCPsTweet-
A study published in #BMCMedInformDecisMak demonstrates the potential of applying machine learning techniques to large-scale health datasets for predicting blood pressure status in low-and middle-income countries. https://t.co/ox7lgEQCUU
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Mashup Score: 262
Background A blockchain can be described as a distributed ledger database where, under a consensus mechanism, data are permanently stored in records, called blocks, linked together with cryptography. Each block contains a cryptographic hash function of the previous block, a timestamp, and transaction data, which are permanently stored in thousands of nodes and never altered. This provides a potential real-world application for generating a permanent, decentralized record of scientific data, taking advantage of blockchain features such as timestamping and immutability. Implementation Here, we propose INNBC DApp, a Web3 decentralized application providing a simple front-end user interface connected with a smart contract for recording scientific data on a modern, proof-of-stake (POS) blockchain such as BNB Smart Chain. Unlike previously proposed blockchain tools that only store a hash of the data on-chain, here the data are stored fully on-chain within the transaction itself as “transacti
Categories: General Medicine News, General HCPsTweet-
An article published in #BMCMedInformDecisMak presents INNBC DApp: a decentralized application providing a simple front-end user interface connected with a smart contract for recording scientific data on a modern, proof-of-stake blockchain. https://t.co/q6BmOQAVIw
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Mashup Score: 0
Background A blockchain can be described as a distributed ledger database where, under a consensus mechanism, data are permanently stored in records, called blocks, linked together with cryptography. Each block contains a cryptographic hash function of the previous block, a timestamp, and transaction data, which are permanently stored in thousands of nodes and never altered. This provides a potential real-world application for generating a permanent, decentralized record of scientific data, taking advantage of blockchain features such as timestamping and immutability. Implementation Here, we propose INNBC DApp, a Web3 decentralized application providing a simple front-end user interface connected with a smart contract for recording scientific data on a modern, proof-of-stake (POS) blockchain such as BNB Smart Chain. Unlike previously proposed blockchain tools that only store a hash of the data on-chain, here the data are stored fully on-chain within the transaction itself as “transacti
Categories: General Medicine News, General HCPsTweet-
An article published in #BMCMedInformDecisMak presents INNBC DApp: a decentralized application providing a simple front-end user interface connected with a smart contract for recording scientific data on a modern, proof-of-stake blockchain. https://t.co/q6BmOQAVIw
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Mashup Score: 2
Background Existing traditional cognitive screening tools for dementia have various limitations, including overreliance on tests assessing verbal memory and, to a lesser extent, on some aspects of executive functioning. Comprehensive neuropsychological assessment is sensitive to impairment but time-intensive and expensive. Virtual reality may provide a dynamic and unique understanding of cognitive performance and increase the ecological validity of cognitive assessment. The use of virtual reality in screening for cognitive function in older persons is promising, but evidence for its use remains sparse. Objective Our primary aim was to examine the feasibility and acceptability of a newly developed, virtual reality assessment module, ‘Leaf Café’, a computer-based program that assesses cognition in an engaging, efficient, and ecologically relevant way. The secondary aim was to assess the ability of the module to discriminate between performances of younger and older adults. Methods A cros
Categories: General Medicine News, General HCPsTweet-
A study published in #BMCMedInformDecisMak assesses the feasibility and acceptability of Leaf Café: a virtual reality tool for the screening of cognitive impairment in older adults. https://t.co/7TkmKcIuws
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An article published in #BMCMedInformDecisMak presents INNBC DApp: a decentralized application providing a simple front-end user interface connected with a smart contract for recording scientific data on a modern, proof-of-stake blockchain. https://t.co/q6BmOQAVIw