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research Neurospectrum: A Geometric and Topological Deep Learning Framework for Uncovering Spatiotemporal Signatures in Neural Activity

3 citations , March 2023 in “bioRxiv (Cold Spring Harbor Laboratory)”

Neurospectrum effectively analyzes neural signals to predict and identify brain activity patterns better than traditional methods.

research Rapid Screening of Anticoagulation Compounds for Biological Target-Associated Adverse Effects Using a Deep-Learning Framework in the Management of Atrial Fibrillation

September 2025 in “Bioengineering”

The framework helps predict adverse effects of blood thinners, improving drug selection for atrial fibrillation.

research Advancing Hair Disease Diagnostics: A Deep Learning Approach Using Inception-ResNet v2 for Multi-Class Classification

December 2024

The model accurately identifies hair diseases using deep learning.

research Amplitude-guided deep reinforcement learning for semi-supervised layer segmentation

January 2026 in “Pattern Recognition”

The new method improves accuracy in segmenting scalp tissue layers.

research KRDQN: An Interpretable Prediction Framework for Adverse Drug Reactions via Knowledge–Graph Reinforced Deep Q-Learning

February 2026 in “Pharmaceuticals”

KRDQN effectively predicts adverse drug reactions with high accuracy and clear explanations.

research A Comprehensive Survey on Vitiligo Detection Using Deep Learning

January 2026 in “ITM Web of Conferences”

Better datasets and methods are needed for reliable vitiligo detection using deep learning.

research How Can Clinicians Leverage Vibe Coding for Machine Learning and Deep Learning Research?

1 citations , October 2025 in “Endocrinology and Metabolism”

Clinicians can use vibe coding to easily engage in machine learning research without needing to know Python.

research Hair Tone Estimation at Roots via Imaging Device with Embedded Deep Learning

3 citations , January 2019 in “Electronic Imaging”

The device accurately estimates natural hair color at the roots in real time.

research Evaluation of Automated Measurement of Hair Density Using Deep Neural Networks

8 citations , January 2022 in “Sensors”

Deep learning can accurately automate hair density measurement, with YOLOv4 performing best.

research Exploring machine learning strategies for single-cell transcriptomic analysis in wound healing

5 citations , January 2025 in “Burns & Trauma”

Machine learning and single-cell analysis improve understanding and treatment of wound healing.

Hair and Scalp Disease Detection Using Machine Learning and Image Processing

research Hair & Scalp Disease Detection Using Machine Learning & Image Processing

4 citations , May 2024 in “INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT”

AI can accurately diagnose hair and scalp conditions and suggest treatments.

research Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders

1 citations , March 2024 in “Skin research and technology”

A new AI model diagnoses hair and scalp disorders with 92% accuracy, better than previous models.

research Optimizing skin disease diagnosis: harnessing online community data with contrastive learning and clustering techniques

1 citations , February 2024 in “npj digital medicine”

Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.

research DEEP REVIEW ON ALOPECIA AREATA DIAGNOSIS FOR HAIR LOSS-RELATED AUTOIMMUNE DISORDER PROBLEM

July 2022 in “International Journal of Applied Pharmaceutics”

Machine learning and deep learning can effectively diagnose alopecia areata.

research Methods of Transfer Learning for Multiclass Hair Disease Categorization

December 2023

Transfer learning with three neural network architectures accurately classifies hair diseases.

research Hair Color Digitization through Imaging and Deep Inverse Graphics

February 2022 in “arXiv (Cornell University)”

A new method accurately captures and renders hair color for real and synthetic images.

research PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery

110 citations , February 2024 in “Journal of Chemical Information and Modeling”

PandaOmics uses AI to find new disease treatment targets and biomarkers.

research Past, present, and future of global research on artificial intelligence applications in dermatology: A bibliometric analysis

12 citations , November 2023 in “Medicine”

AI in dermatology is growing rapidly, showing promise in diagnosing skin conditions as accurately as dermatologists.

research Skin image analysis for detection and quantitative assessment of dermatitis, vitiligo and alopecia areata lesions: a systematic literature review

5 citations , January 2025 in “BMC Medical Informatics and Decision Making”

Computer vision techniques can help detect and assess skin conditions like vitiligo, alopecia areata, and dermatitis.

research Using artificial intelligence to compute Severity of Alopecia Tool scores

5 citations , April 2024 in “JAAD International”

AI can accurately measure hair loss severity in alopecia areata.

research Knowledge Mapping of Drug Repositioning’s Theme and Development

5 citations , April 2023 in “Drug Design Development and Therapy”

Drug repositioning can save time and money but needs more support.

How Good Is Artificial Intelligence at Solving Hairy Problems? A Review of AI Applications in Hair Restoration and Hair Disorders

research How good is artificial intelligence (AI) at solving hairy problems? A review of AI applications in hair restoration and hair disorders

4 citations , January 2021 in “Dermatologic Therapy”

AI is effective in diagnosing and treating hair disorders, including detecting hair loss and scalp conditions with high accuracy, but it should supplement, not replace, doctor-patient interactions.

research Quantitative analysis and development of alopecia areata classification frameworks

2 citations , January 2024 in “Journal of Emerging Investigators”

A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.

research Vitadetect : Vitamin Deficiency Detection

May 2026 in “Open MIND”

VitaDetect is an AI-powered web platform designed to screen for vitamin deficiencies early by analyzing images of nails, tongue, and skin using Convolutional Neural Network (CNN) architectures. It features three specialized deep learning models for body-part-specific analysis: the nail model detects conditions like Bluish Nail and Alopecia Areata linked to Iodine and Vitamin D deficiencies; the tongue model identifies Pale Tongue and Diabetes-related indicators associated with Iron and Vitamin B12 deficiencies; and the skin model recognizes Acne and Carcinoma patterns related to Vitamin D and Vitamin A deficiencies. The platform includes additional features such as personalized diet plans, confidence visualization, health recommendations, doctor discovery, and privacy-preserving image processing.

research Objective quantification of chemotherapy-induced madarosis: a pilot study of an automated computer vision pipeline for eyebrow density assessment

April 2026 in “Scientific Reports”

The tool accurately tracks eyebrow hair loss in chemotherapy patients.

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