Alzheimer’s disease diagnosis using gray matter of T1‐weighted sMRI data and vision transformer.

Background: Alzheimer's Disease (AD) is a progressive neurodegenerative disorder characterized by memory loss and cognitive decline. Traditional diagnostic methods, mainly based on cognitive, memory, and behavioral tests, have limitations, particularly in the early detection of AD. Structural magnetic resonance imaging (sMRI) has emerged as a key tool in understanding the brain changes associated with AD, focusing particularly on alterations in gray matter (GM).

Predicting Individual’s Cognitive Performance Through Multi‐Omics Blood Data Using Hierarchical Input Neural Network ‐ HINN.

Introduction: Detecting declines in cognitive function is a critical global health concern, highlighting the need for timely identification to implement effective intervention strategies. This study investigates the potential of blood‐based biomarkers as accurate and non‐invasive measures of cognitive function. We developed a novel deep learning architecture that integrates multi‐omics data by considering their relationship.

Identifying Alzheimer's disease-associated genes using PhenoGeneRanker.

Alzheimer's disease (AD) is a neurogenerative disease that affects millions worldwide with no effective treatment. Several studies have been conducted to decipher to genomic underpinnings of AD. Due to its complex nature, many genes have been found to be associated with AD.

Feasibility and Acceptability of a Palliative Care Intervention Among Older or Adults with Advanced CKD and their Caregivers.

Background: In non-nephrology settings, specialty Palliative Care (PC) improves decision-making, patient's quality of life (QoL), advance care planning (ACP), and certain indicators of the quality of end-of-life (EoL) care. This pilot RCT explored the feasibility and acceptability of a PC intervention, CKD-EDU, for older adults ≥75 years with eGFR ≤25 ml/min and their caregivers.

Methods: Participants randomized to the control group received standard nephrology care and routine kidney therapy (KT) education, while those randomized to CKD-EDU received a decision aid and met with a PC clinician up to three times to discuss KT decisions and EoL planning.

Palliative Care Acceptability for Older Adults with Advanced CKD: A Qualitative Study of Patients and Nephrologists.

Rationale & Objective: Older adults in the United States often receive kidney therapies that do not align with their goals. Palliative care (PC) specialists are experts in assisting patients with the goals of care discussions and decision support, yet views and experiences of older patients who have received PC while contemplating kidney therapy decisions and their nephrologists remain unexplored. We evaluated the acceptability of CKD-EDU, a PC-based kidney therapy decision support intervention for adults ≥75 years of age.

Predicting peptide properties from mass spectrometry data using deep attention-based multitask network and uncertainty quantification.

Database search algorithms reduce the number of potential candidate peptides against which scoring needs to be performed using a single (i.e. mass) property for filtering.

Comparing Nephrologists' Self-Reported Decision-Making Skills and Treatment Attitudes With Their Patients' Experiences of Making Kidney Therapy Decisions and Receiving Nephrology Care.

Background: Dialysis is often initiated in the United States without exploring patients' preferred decision-making style, and conservative kidney management (CKM) is infrequently presented. To improve kidney therapy (KT) decision-making, research on nephrologists' comfort with various decision-making styles, attitudes towards CKM, and reports of patients' lived experiences with KT decision-making is needed.

Methods: We surveyed 28 nephrologists and 58 of their patients aged ≥75 years.

How can event attribution science underpin financial decisions on Loss and Damage?

With climate extremes hitting nations across the globe, disproportionately burdening vulnerable developing countries, the prompt operation of the Loss and Damage fund is of paramount importance. As decisions on resource disbursement at the international level, and investment strategies at the national level, loom, the climate science community's role in providing fair and effective evidence is crucial. Attribution science can provide useful information for decision makers, but both ethical implications and deep uncertainty cannot be ignored.

Making MS Omics Data ML-Ready: SpeCollate Protocols.

The increasing complexity and volume of mass spectrometry (MS) data have presented new challenges and opportunities for proteomics data analysis and interpretation. In this chapter, we provide a comprehensive guide to transforming MS data for machine learning (ML) training, inference, and applications. The chapter is organized into three parts.

Exploring Patient Needs and Preferences in CKD Education: A Cross-Sectional Survey Study.

Key Points: This largest to date patient survey study explores what patients with kidney disease want to know about treatments, such as dialysis or conservative management. A surprising number of patients want extensive doctor-like education, but are willing to spend only several hours on education. Patients are notably open to online and digital educational modalities—technology may allow for individualized and ongoing patient education.

Uncovering Patient and Caregiver Goals for Goal-Concordant Care in Kidney Therapy Decisions.

Context: In kidney therapy (KT) decisions, goal-concordant decision-making is recognized to be important, yet alignment with patients' goals during dialysis initiation is not always achieved.

Objectives: To explore older patients' and caregivers' hopes, goals, and fears related to KT and communication of these elements with members of their health care team.

Methods: The study included patients aged ≥75 years with an estimated glomerular filtration rate ≤25 mL/min/1.

PVTAD: ALZHEIMER'S DISEASE DIAGNOSIS USING PYRAMID VISION TRANSFORMER APPLIED TO WHITE MATTER OF T1-WEIGHTED STRUCTURAL MRI DATA.

Alzheimer's disease (AD) is a neurodegenerative disorder, and timely diagnosis is crucial for early interventions. AD is known to have disruptive local and global brain neural connections that may be instrumental in understanding and extracting specific biomarkers. Previous machine-learning approaches are mostly based on convolutional neural network (CNN) and standard vision transformer (ViT) models which may not sufficiently capture the multidimensional local and global patterns that may be indicative of AD.

GPU-acceleration of the distributed-memory database peptide search of mass spectrometry data.

Database peptide search is the primary computational technique for identifying peptides from the mass spectrometry (MS) data. Graphical Processing Units (GPU) computing is now ubiquitous in the current-generation of high-performance computing (HPC) systems, yet its application in the database peptide search domain remains limited. Part of the reason is the use of sub-optimal algorithms in the existing GPU-accelerated methods resulting in significantly inefficient hardware utilization.

Confounding Effects on the Performance of Machine Learning Analysis of Static Functional Connectivity Computed from rs-fMRI Multi-site Data.

Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive imaging technique widely used in neuroscience to understand the functional connectivity of the human brain. While rs-fMRI multi-site data can help to understand the inner working of the brain, the data acquisition and processing of this data has many challenges. One of the challenges is the variability of the data associated with different acquisitions sites, and different MRI machines vendors.

Development and Acceptability of a Kidney Therapy Decision Aid for Patients Aged 75 Years and Older: A Design-Based Research Involving Patients, Caregivers, and a Multidisciplinary Team.

Rationale & Objective: Many older adults prefer quality of life over longevity, and some prefer conservative kidney management (CKM) over dialysis. There is a lack of patient-decision aids for adults aged 75 years or older facing kidney therapy decisions, which not only include information on dialysis and CKM but also encourage end-of-life planning. We iteratively developed a paper-based patient-decision aid for older people with low literacy and conducted surveys to assess its acceptability.

Prevalence and Correlates of Preference-Concordant Care Among Hospitalized People Receiving Maintenance Dialysis.

Key Points: A large proportion of hospitalized patients receiving dialysis report not receiving preference-concordant care. Hospitalized patients on dialysis desiring a comfort-oriented medical plan were likely to report receiving preference-concordant care.

Background: Preference-concordant care is a cornerstone of high-quality medical decision-making, yet the prevalence and correlates of preference-concordant care have not been well-studied in patients receiving dialysis.

PPAD: A deep learning architecture to predict progression of Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative disease that affects millions of people worldwide. Mild cognitive impairment (MCI) is an intermediary stage between cognitively normal (CN) state and AD. Not all people who have MCI convert to AD.

Description of Dissolved Organic Matter Transformational Networks at the Molecular Level.

Dissolved Organic Matter (DOM) is an important component of the global carbon cycle. Unscrambling the structural footprint of DOM is key to understand its biogeochemical transformations at the mechanistic level. Although numerous studies have improved our knowledge of DOM chemical makeup, its three-dimensional picture remains largely unrevealed.

Racial Disparities in Health Beliefs and Advance Care Planning Among Patients Receiving Maintenance Dialysis.

Context: Among people receiving maintenance dialysis, little is known about racial disparities in the occurrence of prognostic discussions, beliefs about future health, and completion of advance care planning (ACP) documents.

Objectives: We examined whether Black patients receiving maintenance dialysis differ from White patients in prognostic discussions, beliefs about future health, and completion of ACP-related documents.

Methods: We surveyed adult patients receiving maintenance dialysis from seven dialysis units in Cleveland, Ohio, and hospitalized patients at a tertiary care hospital in Cleveland.

Classification of Autism Spectrum Disorder Using rs-fMRI data and Graph Convolutional Networks.

Autism spectrum disorder (ASD) affects large number of children and adults in the US, and worldwide. Early and quick diagnosis of ASD can improve the quality of life significantly both for patients and their families. Prior research provides strong evidence that structural and functional magnetic resonance imaging (MRI) data collected from individuals with ASD exhibit distinguishing characteristics that differ in local and global, spatial and temporal neural patterns of the brain - and therefore can be used for diagnostic purposes for various mental disorders.