Bioinformatics and Medical Applications

202 199

203 200

204 201

205 202

206 203

207 204

208 205

209 206

210 207

211 208

212 209

213 210

214 211

215 212

216 213

217 215

218 216

219 217

220 218

221 219

222 220

223 221

224 222

225 223

226 224

227 225

228 226

229 227

230 228

231 229

232 230

233 231

234 232

235 233

236 234

237 235

238 236

239 237

240 238

241 239

242 240

243 241

244 242

245 243

246 244

247 245

248 246

249 247

250 248

251 249

252 250

253 251

254 252

255 253

256 254

257 255

258 256

259 257

260 258

261 259

262 260

263 261

264 262

265 263

266 264

267 265

268 266

269 267

270 269

271 270

272 271

273 272

274 273

275 274

276 275

277 276

278 277

279 278

280 279

281 280

282 281

283 282

284 283

285 284

286 285

287 286

288 287

289 288

290 289

291 290

292 291

293 292

294 293

295 294

296 295

297 296

298 297

299 298

300 299

301 300

302 301

303 302

304 303

305 304

306 305

307 306

308 307

309 308

310 309

311 310

312 311

313 312

314 313

315 315

316 316

317 317

318 318

319 319

320 320

321 321

Edited by

A. Suresh

S. Vimal

Y. Harold Robinson

Dhinesh Kumar Ramaswami

and

R. Udendhran

This edition first published 2022 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA

© 2022 Scrivener Publishing LLC

For more information about Scrivener publications please visit www.scrivenerpublishing.com.

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.

Wiley Global Headquarters111 River Street, Hoboken, NJ 07030, USA

For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com.

Limit of Liability/Disclaimer of WarrantyWhile the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials, or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read.

Library of Congress Cataloging-in-Publication Data

ISBN 978-1-119-79183-6

Cover image: Pixabay.ComCover design by Russell Richardson

Set in size of 11pt and Minion Pro by Manila Typesetting Company, Makati, Philippines

Printed in the USA

10 9 8 7 6 5 4 3 2 1

This book features bioinformatics applications in the medical field that employ deep learning algorithms to analyze massive biological datasets using computational approaches and the latest cutting-edge technologies to capture and interpret biological data. In addition to delivering the various bioinformatics computational methods used to identify diseases at an early stage, it also collects cutting-edge resources in a single source designed to enlighten the reader with topics centered on computer science, mathematics, and biology. Since bioinformatics is critical for data management in the current fields of biology and medicine, this book explains the important tools used by bioinformaticians and examines how they are used to evaluate biological data in order to advance disease knowledge.

As shown in the chapter-by-chapter synopsis that follows, the editors of this book have curated a distinguished group of perceptive and concise chapters that reflect the current state of medical treatments and systems and offer emerging solutions for a more personalized approach to the healthcare field. Since applying deep learning techniques for data-driven solutions in health information allows automated analysis, this method can be more advantageous in addressing the problems arising from medical- and health-related information.

– Chapter 1, “Probabilistic Optimization of Machine Learning Algorithms for Heart Disease Prediction,” discusses the ensemble learning that overcomes the limitations of a single algorithm, such as bias and variance, by using a multitude of algorithms. It highlights the importance of ensemble techniques in improving the forecast accuracy and displaying an acceptable performance in disease prediction. Additionally, the authors have worked on a procedure to further improve the accuracy of the ensemble method post application by focusing on the wrongly classified records and using probabilistic optimization to select pertinent columns by increasing their weight and doing a reclassification which would result in further improved accuracy.

– Chapter 2, “Cancerous Cells Detection in Lung Organs of the Human Body: IoT-Based Healthcare 4.0 Approach,” analyzes three types of cancer—squamous cell carcinoma, adenocarcinoma, and large cell carcinoma—derived from lung tissue, and investigates how AI can customize treatment choices for lung cancer patients.

– Chapter 3, “Computational Predictors of the Predominant Protein Function: SARS-CoV-2 Case,” describes the main molecular features of SARS-CoV-2 that cause COVID-19 disease, as well as a high-efficiency computational prediction called the polarity index method. Furthermore, it presents a molecular classification of the RNA-virus and DNA-virus families with results obtained by the proposed non-supervised method focusing on the linear representation of proteins.

– Chapter 4, “Deep Learning in Gait Abnormality Detection: Principles and Illustrations,” discusses cerebral palsy, a medical condition which is marked by weakened muscle coordination and other dysfunctions. This chapter proposes a deep learning technique, including support vector machines, multilayer perceptron, vanilla long short-term memory, and bi-directional LSTM, to diagnose cerebral palsy gait.