Multimodal machine learning in precision health: A sco** review
Abstract Machine learning is frequently being leveraged to tackle problems in the health
sector including utilization for clinical decision-support. Its use has historically been focused …
sector including utilization for clinical decision-support. Its use has historically been focused …
Integrating multi-omics data with EHR for precision medicine using advanced artificial intelligence
With the recent advancement of novel biomedical technologies such as high-throughput
sequencing and wearable devices, multi-modal biomedical data ranging from multi-omics …
sequencing and wearable devices, multi-modal biomedical data ranging from multi-omics …
A survey on deep learning in medicine: Why, how and when?
New technologies are transforming medicine, and this revolution starts with data. Health
data, clinical images, genome sequences, data on prescribed therapies and results …
data, clinical images, genome sequences, data on prescribed therapies and results …
Attention-based multimodal fusion with contrast for robust clinical prediction in the face of missing modalities
Objective: With the increasing amount and growing variety of healthcare data, multimodal
machine learning supporting integrated modeling of structured and unstructured data is an …
machine learning supporting integrated modeling of structured and unstructured data is an …
Development and validation of a personalized model with transfer learning for acute kidney injury risk estimation using electronic health records
K Liu, X Zhang, W Chen, SL Alan, JA Kellum… - JAMA Network …, 2022 - jamanetwork.com
Importance Acute kidney injury (AKI) is a heterogeneous syndrome prevalent among
hospitalized patients. Personalized risk estimation and risk factor identification may allow …
hospitalized patients. Personalized risk estimation and risk factor identification may allow …
Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup
Acute kidney injury (AKI), which is a common complication of acute illnesses, affects the
health of individuals in community, acute care and post-acute care settings. Although the …
health of individuals in community, acute care and post-acute care settings. Although the …
[HTML][HTML] Deep phenoty**: embracing complexity and temporality—towards scalability, portability, and interoperability
Clinical data are the basic staple of health learning [1]. The rapidly growing interoperable
clinical datasets, including electronic health records (EHR), administrative and claims …
clinical datasets, including electronic health records (EHR), administrative and claims …
Promises of big data and artificial intelligence in nephrology and transplantation
Kidney diseases form part of the major health burdens experienced all over the world.
Kidney diseases are linked to high economic burden, deaths, and morbidity rates. The great …
Kidney diseases are linked to high economic burden, deaths, and morbidity rates. The great …
Nanotechnology‐Based Sensitive Biosensors for COVID‐19 Prediction Using Fuzzy Logic Control
Increasing the growth of big data, particularly in healthcare‐Internet of Things (IoT) and
biomedical classes, tends to help patients by identifying the disease early through methods …
biomedical classes, tends to help patients by identifying the disease early through methods …
Machine learning models for predicting acute kidney injury: a systematic review and critical appraisal
Background The number of studies applying machine learning (ML) to predict acute kidney
injury (AKI) has grown steadily over the past decade. We assess and critically appraise the …
injury (AKI) has grown steadily over the past decade. We assess and critically appraise the …