A Novel Machine Learning Optimization for Early Alzheimer's Disease Detection

Alzheimer’s and dementia are progressive neurological disorders that severely affect memory, thinking ability, behavior, and the capacity to perform everyday activities. Patients suffering from these conditions often struggle with recognizing familiar people, remembering important tasks such as medication intake, and managing routine activities independently. This creates a high level of dependency on caregivers, leading to emotional, physical, and mental stress for both patients and their families.The proposed system aims to provide an intelligent assistive solution to support individuals affected by Alzheimer’s and dementia in their daily lives. It focuses on improving patient safety, enhancing independence, and reducing caregiver burden through automated assistance and monitoring. The system is designed to help in recognizing known individuals, managing daily reminders, tracking emotional states, and suggesting suitable activities based on user needs.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-28
DOI
https://doi.org/10.5281/zenodo.19861478
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Novel Machine Learning Optimization for Early Alzheimer's Disease Detection

Shubham Dilip Rane, Dr. Pratiksha Chafle
Zenodo (CERN European Organization for Nuclear Research)
Dementia and Cognitive Impairment Research
article

A Novel Machine Learning Optimization for Early Alzheimer's Disease Detection

Shubham Dilip Rane, Dr. Pratiksha Chafle
article en

Abstract

Alzheimer’s and dementia are progressive neurological disorders that severely affect memory, thinking ability, behavior, and the capacity to perform everyday activities. Patients suffering from these conditions often struggle with recognizing familiar people, remembering important tasks such as medication intake, and managing routine activities independently. This creates a high level of dependency on caregivers, leading to emotional, physical, and mental stress for both patients and their families.The proposed system aims to provide an intelligent assistive solution to support individuals affected by Alzheimer’s and dementia in their daily lives. It focuses on improving patient safety, enhancing independence, and reducing caregiver burden through automated assistance and monitoring. The system is designed to help in recognizing known individuals, managing daily reminders, tracking emotional states, and suggesting suitable activities based on user needs.

Zenodo (CERN European Organization for Nuclear Research)
Sant Gadge Baba Amravati University (IN)
Openalex Percentile: Top 5%
Dementia and Cognitive Impairment Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.