Aakanksha Rana

Aakanksha Rana

Massachusetts Institute of Technology

H-index: 12

North America-United States

About Aakanksha Rana

Aakanksha Rana, With an exceptional h-index of 12 and a recent h-index of 10 (since 2020), a distinguished researcher at Massachusetts Institute of Technology, specializes in the field of Medical Imaging, Digital Pathology, Computer Vision, Deep Learning, Immersive Technologies.

His recent articles reflect a diverse array of research interests and contributions to the field:

FDA-approved machine learning algorithms in neuroradiology: a systematic review of the current evidence for approval

Pain Prediction Using Digital Phenotyping Speech Data for Neurological Spine Disease Patients

444 Extraction and Analysis of Speech Features to Understand Audio Phenotypes of Pain

Traditional Machine Learning Methods versus Deep Learning for Meningioma Classification, Grading, Outcome Prediction, and Segmentation: A Systematic Review and Meta-Analysis

Passive data use for ethical digital public health surveillance in a postpandemic world

A systematic review of federated learning applications for biomedical data

Daily pain prediction using smartphone speech recordings of patients with spine disease

Artificial Intelligence and Healthcare Ethics

Aakanksha Rana Information

University

Position

___

Citations(all)

561

Citations(since 2020)

470

Cited By

218

hIndex(all)

12

hIndex(since 2020)

10

i10Index(all)

15

i10Index(since 2020)

10

Email

University Profile Page

Massachusetts Institute of Technology

Google Scholar

View Google Scholar Profile

Aakanksha Rana Skills & Research Interests

Medical Imaging

Digital Pathology

Computer Vision

Deep Learning

Immersive Technologies

Top articles of Aakanksha Rana

Title

Journal

Author(s)

Publication Date

FDA-approved machine learning algorithms in neuroradiology: a systematic review of the current evidence for approval

Alexander G Yearley

Caroline MW Goedmakers

Armon Panahi

Aakanksha Rana

Joanne Doucette

...

2023/6/7

Pain Prediction Using Digital Phenotyping Speech Data for Neurological Spine Disease Patients

Akiro Duey

Aakanksha Rana

Francesca Siddi

Helweh Hussein

J.P. Onnela

...

2023/4

444 Extraction and Analysis of Speech Features to Understand Audio Phenotypes of Pain

Neurosurgery

Akiro Duey

Aakanksha Rana

Helweh Hussein

Francesca Siddi

JP Onnela

...

2023/4/1

Traditional Machine Learning Methods versus Deep Learning for Meningioma Classification, Grading, Outcome Prediction, and Segmentation: A Systematic Review and Meta-Analysis

Krish M Maniar

Philipp Lassarén

Aakanksha Rana

Yuxin Yao

Ishaan A Tewarie

...

2023/8/12

Passive data use for ethical digital public health surveillance in a postpandemic world

Journal of Medical Internet Research

John L Kilgallon

Ishaan Ashwini Tewarie

Marike LD Broekman

Aakanksha Rana

Timothy R Smith

2022/2/15

A systematic review of federated learning applications for biomedical data

Matthew G Crowson

Dana Moukheiber

Aldo Robles Arévalo

Barbara D Lam

Sreekar Mantena

...

2022/5/19

Daily pain prediction using smartphone speech recordings of patients with spine disease

Neurosurgery

Akiro H Duey

Aakanksha Rana

Francesca Siddi

Helweh Hussein

Jukka-Pekka Onnela

...

2023/9/1

Artificial Intelligence and Healthcare Ethics

Traumatic Brain Injury: Science, Practice, Evidence and Ethics

Aakanksha Rana

Caroline MW Goedmakers

Timothy R Smith

2021

Deep neural networks allow expert-level brain meningioma detection, segmentation and improvement of current clinical practice

Scientific Reports

Alessandro Boaro

Jakub R Kaczmarzyk

Vasileios K Kavouridis

Maya Harary

Marco Mammi

...

2022/9/14

Deep learning for adjacent segment disease at preoperative MRI for cervical radiculopathy

Radiology

Caroline MW Goedmakers

Asad M Lak

Akiro H Duey

Alexander W Senko

Omar Arnaout

...

2021/12

Towards the implementation of eco-epidemiological models for dengue in Colombia using machine learning and satellite images: Policy advocacy and open data repositories.

Biomédica: Revista del Instituto Nacional de Salud

Juan Sebastián Osorio-Valencia

David Restrepo

Cheng Che Tsai

Sebastián Andrés Cajas

Dana Moukheiber

...

2021/11/2

Quality Assessment of Super-Resolved Omnidirectional Image Quality Using Tangential Views

arXiv preprint arXiv:2101.10396

Cagri Ozcinar

Aakanksha Rana

2021/1/25

Team-Based Decision-Making in Traumatic Brain Injury

Traumatic Brain Injury: Science, Practice, Evidence and Ethics

Timothy R Smith

Brittany M Stopa

Caroline MW Goedmakers

Aakanksha Rana

2021

Sub-pixel back-projection network for lightweight single image super-resolution

arXiv preprint arXiv:2008.01116

Supratik Banerjee

Cagri Ozcinar

Aakanksha Rana

Aljosa Smolic

Michael Manzke

2020/8/3

See List of Professors in Aakanksha Rana University(Massachusetts Institute of Technology)

Co-Authors

H-index: 59
Aljosa Smolic

Aljosa Smolic

Trinity College

H-index: 56
Nikos Komodakis

Nikos Komodakis

University of Crete

H-index: 24
Omar Arnaout

Omar Arnaout

Harvard University

H-index: 20
Praveer Singh

Praveer Singh

Harvard University

H-index: 19
Matthew G. Crowson

Matthew G. Crowson

Harvard University

H-index: 10
alessandro boaro

alessandro boaro

Università degli Studi di Verona

academic-engine